Post Syndicated from Crosstalk Solutions original https://www.youtube.com/watch?v=WffbOrF8hG8
5 Ways to Use Event Notifications to Advance Your Media Better, Faster
Post Syndicated from Jeremy Milk original https://www.backblaze.com/blog/5-ways-to-use-event-notifications-to-advance-your-media-better-faster/

In the hurry-up-and-wait world of media production, anything you can do to speed through the hurry-ups and avoid or shorten the waits is not just a gift—it’s an advantage that can mean happier team members, delighted clients and fans, and more revenue.
Backblaze Event Notifications can help.This new B2 Cloud Storage feature can help you streamline a range of your production tasks—like automatically starting transcoding of video and distributing new images—across your preferred workflow tools.
Today, I’m sharing five ways you can use Backblaze Event Notifications to operationalize media production efficiencies. If you’re interested in Event Notifications for applications, check out this post; and stay tuned for a future post on how to use Event Notifications for IT backup.
Event Notifications for media production: Simplified automation
Event Notifications monitors your B2 Cloud Storage for data changes that you designate—think raw video uploads, content version updates, deletions, etc.—and delivers near real-time alerts where you want them about these changes. These alerts can be used to create awareness faster, and even more powerfully, to initiate streamlined end-to-end processes that can save you time and hassle, and avoid unnecessary manual tasks and/or the cost of complex intermediaries.
What are webhooks?
Webhooks, if you’re not familiar with the term, are HTTP-based callback functions that enable event-based communications between software applications. Backblaze Event Notifications can uniquely work with any external service that accepts webhooks. This means you can use it to your advantage across your media production workflow—and this is novel when most vendors’ alerts features are limited to closed ecosystems or require significant and sometimes costly workarounds to communicate beyond a limited set of production tools.
Top 5 use cases for media production
Here are specific, practical ways people producing and managing media can take advantage of Event Notifications for immediate benefits.
1. New content processing
Event Notifications can be used to trigger tasks immediately after new content is uploaded. Imagine one of your team members uploads a video or image: Event Notifications can be sent to a transcoding service to format it and a tagging service to categorize it for better content organization. Set up to furthermore extract valuable metadata too—all in near real time, without manual intervention.
General workflow (abbreviated)

By automating these processes, companies can ensure that user-generated content is formatted correctly, appropriately tagged, and moderated without delay. This not only saves time but guarantees a consistent user experience.
What’s more, you can even go full Jedi Knight and handle errors programmatically with Event Notifications logic that triggers reprocessing tasks whenever issues arise.
2. Integrated alerts in go-to tools
Event Notifications can easily integrate with your communication tools like Slack and productivity tools like Zapier, to inform internal and external stakeholders of updates without them needing to check for them manually. Users have told us this is a great way to keep people updated when assets are added, updated, or advanced to key stages in production and post cycles—setting them up to consider taking downstream actions that don’t lend themselves to further process automation.
Asset change announcement workflow

Additionally, for teams using workflow tools such as Zapier to connect various services, Event Notifications makes it simple to trigger actions across multiple platforms, enabling powerful, automated workflows with your data in B2 Cloud Storage.
3. Over-the-top (OTT) streaming automation
Regardless of whether your streaming model is AVOD, TVOD, or SVOD, Event Notifications can help automate processing and distribution workflows. Users can enable them so that every time a new title is added to B2 Cloud Storage, it then triggers alerts that initiate transcoding, compression, and prep for delivery or playback via content delivery network (CDN).
OTT streaming platform workflow

4. Backup completion monitoring
An important (if unglamorous) aspect of managing media is backing it up for extra safekeeping. After all, it’s a precious asset worth a lot of money now and later. So whether you back up nightly, monthly, at project’s end, or on some other cadence, with Event Notifications, customers can set up to receive updates when their media backups are successfully uploaded to a Backblaze B2 Bucket—providing peace of mind when data is protected.
We’ve also had a few users already tell us that not seeing backup completion alerts when expected helped them realize that they had other, previously unknown workflow hiccups to address.
Backup complete workflow

Tangentially related, media organizations are also using Backblaze Cloud Replication to programmatically store their content to two or more geographically distributed locations for added protection—this isn’t the same as Event Notifications, but is another automation tool for enhancing your protection posture.
5. Monitor data usage
Since Event Notifications messages are sent within seconds of files being uploaded and deleted, and they contain the size of the file in question, you can easily and reliably track your data usage in near real time, helping you identify trends and potential issues. For example, if you know large raw files are coming in and then messages indicating much smaller than expected file sizes were uploaded, it can alert you to begin to QC it.
We’ve also seen such data monitoring prove highly beneficial to IT personnel who support them because the near real-time monitoring allows faster responses to situations as they are happening, thereby mitigating risks, reducing costs, and/or nipping issues in the bud so the production teams remain disruption and distraction free.
Monitoring workflow

Beyond these example use cases, Event Notifications opens up a wide range of possibilities for automating and optimizing workflows. This flexibility makes it easy to automate how your infrastructure interacts with and reacts to file changes in B2 Cloud Storage, simplifying workflows across your distributed services. So go ahead and get creative—and please do share with us the cool things you’re doing with Event Notifications.
Why Event Notifications matter for production workflows
The benefits of real-time notifications extend beyond simply saving time—they transform the way teams work, automate processes, and reduce the margin for error.
- Awareness: Instant notifications for uploads, updates, or deletions keep everyone on the same page.
- Actionable insights: Real-time alerts provide critical information that helps make informed decisions quickly.
- Flexibility: Direct connections to services like media asset managers (MAMs), transcoding applications, and CDNs mean more choice to stick with your preferred stack and less lock-in to specific vendors or tools.
- Cost efficiency: Automating tasks like media transcoding, data processing, or content delivery reduces the need for manual labor, saving on operational costs and freeing up resources for other strategic initiatives.
Improved security: By instantly alerting teams to changes or unusual activity, Event Notifications help maintain data integrity and support proactive security measures.
How Event Notifications compares
Unlike other offerings like Amazon’s messaging services, which are limited to specific ecosystems, Backblaze Event Notifications integrates directly with any service that accepts webhooks, offering true flexibility and avoiding vendor lock-in.
Event Notifications is also designed for at-least-once delivery, ensuring critical notifications are not missed. This reliability is important for teams building workflows that require precision and a level of consistency their end users expect.
The pricing for Event Notifications is simple and transparent. Backblaze B2 Reserve customers enjoy unlimited free Event Notifications, while pay-as-you-go Backblaze B2 customers enjoy 2,500 calls per day free and then $0.004 per 10,000 transactions. This straightforward pricing applies no matter the service receiving the notification. This enables businesses to confidently scale their event-driven workflows, knowing exactly what to expect in terms of costs, regardless of the services they choose to integrate with.
Ready to add automation to your media tasks?
For existing customers working with a Backblaze account manager, Event Notifications is already enabled for you, and your account manager can assist with any questions. If you’re an existing customer not currently working with an account manager, please contact our Support team to request access to Event Notifications.
New customers can contact our Sales team to learn more about how Event Notifications can streamline workflows and how to get started.
Once Event Notifications are enabled, log in to your Backblaze B2 account, navigate to the Buckets page, and click on the Event Notifications section. From there, you can set up notification rules for the events you want to track or configure notifications using our API.
For detailed instructions and best practices, visit our Event Notifications documentation.
The post 5 Ways to Use Event Notifications to Advance Your Media Better, Faster appeared first on Backblaze Blog | Cloud Storage & Cloud Backup
Harper Steele on crossing the country with Will Ferrell
Post Syndicated from Talks at Google original https://www.youtube.com/watch?v=epVaUUuOuKc
[$] Arch Linux finally starts licensing PKGBUILDs
Post Syndicated from jzb original https://lwn.net/Articles/998778/
Arch Linux is popular as a base
for other Linux distributions; examples of Arch-derivatives include EndeavourOS, Manjaro, Parabola, and SteamOS.
There’s one small problem: the control files used to describe how to build
packages for Arch Linux have no stated license. That creates a bit of
uncertainty about the rights and responsibilities for the downstream
derivatives. So far, that doesn’t seem to have been a problem, nor has
it stopped other projects from assuming that reuse is
allowed. However, the Arch project is looking to add some clarity by
explicitly assigning a liberal license to its package
sources. Currently the project is in the process of reaching out to
contributors to see if they have any objections.
Analyzing your AWS Cost Explorer data with Amazon Q Developer: Now Generally Available
Post Syndicated from Riya Dani original https://aws.amazon.com/blogs/devops/analyzing-your-aws-cost-explorer-data-with-amazon-q-developer-now-generally-available/
We are excited to announce the general availability of the cost analysis capability in Amazon Q Developer. This powerful feature integrates Q Developer’s natural language processing capabilities with AWS Cost Explorer, revolutionizing how you analyze and understand your AWS costs. Initially launched in preview on April 30, 2024, the Amazon Q cost analysis capability now offers enhanced functionality, allowing users to gain deeper insights into their cloud spending through simple, conversational interactions.
In this blog, we will highlight the key features and capabilities of analyzing your Cost Explorer data with Amazon Q Developer, including its ability to handle complex cost queries, provide context-aware responses, and offer actionable insights into your AWS spending.
Simplifying Cost Analysis with Natural Language Queries
At the heart of Amazon Q for AWS cost management is its ability to understand and respond to natural language queries. This feature reduces the learning curve to get valuable cost insights from Cost Explorer.
Users can now simply type their questions in plain English, such as:
- “What were my top 5 most expensive services last month?”
- “How much did my S3 costs increase between Q1 and Q2?”
- “Did we receive any credits last quarter, and if so, how much?”
Q Developer interprets these questions, processes the relevant data, and provides detailed, actionable insights.
For our first example, imagine you’re a Cloud Architect who wants to understand the cost implications of recent architectural changes. You could open Amazon Q in the AWS Management Console and enter a prompt such as: “Show me the breakdown of EC2 costs by instance type for the last 30 days”
Figure 1: Q Developer listing breakdown of EC2 instance types for a specific time period
As shown in Figure 1, Q Developer provides a detailed breakdown of the EC2 instance types for the last 30 days.
Let’s consider another scenario. A FinOps professional responsible for reporting on cloud costs across multiple departments could ask “What were last month’s costs broken down by Cost Category “Cost Center”?
Figure 2: Q Developer delivers a comprehensive cost analysis breakdown by cost category for the previous month.
Figure 2 showcases Q Developer’s capability to instantly generate detailed cost insights based on custom categories. This feature empowers users to make data-driven decisions for more effective cost allocation and budget planning.
Finally, let’s say you are an IT professional who wants to understand what your future costs will look like, based on current workloads and recent trends. You could ask “What are my forecasted costs for Q1 of next year?”
Figure 3: Q Developer provides forecasted cost data from AWS Cost Explorer.
Figure 3 shows Q Developer ’s ability to provide both historical and forecasted costs, helping customers plan and predict their spending.
Here are some other examples of questions you can now explore when analyzing your Cost Explorer data with Amazon Q:
- What percentage of our total costs last month were attributed to tag key = “Environment”, value = “Dev”?
- Which services had the highest month-over-month cost increase in September?“
- Which linked accounts spent the most last month?
- What is our forecasted spend for the next three months?
- What were my costs broken down by tag key “Project”?”
Verifying data and diving deeper
Q Developer provides transparency on the specific AWS Cost Explorer parameters that were used to retrieve the data to answer your questions. This transparency allows you to verify that the data presented is exactly what you were looking for. Additionally, each response includes a link to a matching view in AWS Cost Explorer, so you can dive deeper and visualize your data.
Figure 4: Q Developer provides a link to a matching view in AWS Cost Explorer.
Figure 4 demonstrates how Q Developer bridges natural language queries with AWS Cost Explorer’s powerful visualization capabilities. This integration allows users to effortlessly transition from conversational insights to comprehensive graphical representations of their cost data, facilitating more thorough analysis and informed decision-making.
Conclusion
The general availability of Q Developer for AWS Cost Management marks a significant milestone in simplifying cloud financial management. By leveraging natural language processing and context-aware responses, Amazon Q makes it easier than ever for users across various roles – from FinOps professionals to application developers– to gain valuable insights into their AWS spending.
These new features streamline the process of cost analysis and forecasting, improving efficiency and enabling data-driven decision-making for AWS users. We encourage you to explore Amazon Q for cost analysis and experience firsthand how it can transform your approach to cloud cost management.
To get started with cost analysis in Q Developer, simply log in to the AWS Management Console and click on Amazon Q icon on the right side of the console. For more information on pricing and availability, please visit our Cost analysis in Amazon Q Developer documentation.
Cloudflare incident on November 14, 2024, resulting in lost logs
Post Syndicated from Jamie Herre original https://blog.cloudflare.com/cloudflare-incident-on-november-14-2024-resulting-in-lost-logs
On November 14, 2024, Cloudflare experienced an incident which impacted the majority of customers using Cloudflare Logs. During the roughly 3.5 hours that these services were impacted, about 55% of the logs we normally send to customers were not sent and were lost. We’re very sorry this happened, and we are working to ensure that a similar issue doesn’t happen again.
This blog post explains what happened and what we’re doing to prevent recurrences. Also, the systems involved and the particular class of failure we experienced will hopefully be of interest to engineering teams beyond those specifically using these products.
Failures within systems at scale are inevitable, and it’s essential that subsystems protect themselves from failures in other parts of the larger system to prevent cascades. In this case, a misconfiguration in one part of the system caused a cascading overload in another part of the system, which was itself misconfigured. Had it been properly configured, it could have prevented the loss of logs.
Cloudflare’s network is a globally distributed system enabling and supporting a wide variety of services. Every part of this system generates event logs which contain detailed metadata about what’s happening with our systems around the world. For example, an event log is generated for every request to Cloudflare’s CDN. Cloudflare Logs makes these event logs available to customers, who use them in a number of ways, including compliance, observability, and accounting.
On a typical day, Cloudflare sends about 4.5 trillion individual event logs to customers. Although this represents less than 10% of the over 50 trillion total customer event logs processed, it presents unique challenges of scale when building a reliable and fault-tolerant system.
Cloudflare’s network is composed of tens of thousands of individual servers, network hardware components, and specialized software programs located in over 330 cities around the world. Although Cloudflare’s Edge Log Delivery product will send customers their event logs directly from each server, most customers opt not to do this because doing so will create significant complication and cost at the receiving end.
By analogy, imagine the postal service ringing your doorbell once for each letter instead of once for each packet of letters. With thousands or millions of letters each second, the number of separate transactions that would entail becomes prohibitive.
Fortunately, we also offer Logpush, which collects and pushes logs to customers in more predictable file sizes and which scales automatically with usage. In order to provide this feature several services work together to collect and push the logs, as illustrated in the diagram below:

Logfwdr is an internal service written in Golang that accepts event logs from internal services running across Cloudflare’s global network and forwards them in batches to a service called Logreceiver. Logfwdr handles many different types of event logs, and one of its responsibilities is to determine which event logs should be forwarded and where they should be sent based on the type of event log, which customers it represents, and associated rules about where it should be processed. Configuration is provided to Logfwdr to enable it to make these determinations.
Logreceiver (also written in Golang) accepts the batches of logs from across Cloudflare’s global network and further sorts them depending on the type of event and its purpose. For Cloudflare Logs, Logreceiver demultiplexes the batches into per-customer batches and forwards them to be buffered by Buftee. Currently, Logreceiver is handling about 45 PB (uncompressed) of customer event logs each day.
It’s common for data pipelines to include a buffer. Producers and consumers of the data might be operating at different cadences, and parts of the pipeline will experience variances in how quickly they can process information. Using a buffer makes it easier to manage these situations, and helps to prevent data loss if downstream consumers are broken. It’s also convenient to have a buffer that supports multiple downstream consumers with different cadences (like the pipe fitting function of a tee.)
At Cloudflare, we use an internal system called Buftee (written in Golang) to support this combined function. Buftee is a highly distributed system which supports a large number of named “buffers”. It supports operating on named “prefixes” (collections of buffers) as well as multiple representations/resolutions of the same time-indexed dataset. Using Buftee makes it possible for Cloudflare to handle extremely high throughput very efficiently.
For Cloudflare Logs, Buftee provides buffers for each Logpush job, containing 100% of the logs generated by the zone or account referenced by each job. This means that failure to process one customer’s job will not affect progress on another customer’s job. Handling buffers in this way avoids “head of line” blocking and also enables us to encrypt and delete each customer’s data separately if needed.
Buftee typically handles over 1 million buffers globally. The following is a snapshot of the number of buffers managed by Buftee servers in the period just prior to the incident.

Logpush is a Golang service which reads logs from Buftee buffers and pushes the results in batches to various destinations configured by customers. A batch could end up, for example, as a file in R2. Each job has a unique configuration, and only jobs that are active and configured will be pushed. Currently, we push over 600 million such batches each day.
On November 14, 2024, we made a change to support an additional dataset for Logpush. This required adding a new configuration to be provided to Logfwdr in order for it to know which customers’ logs to forward for this new stream. Every few minutes, a separate system re-generates the configuration used by Logfwdr to decide which logs need to be forwarded. A bug in this system resulted in a blank configuration being provided to Logfwdr.
This bug essentially informed Logfwdr that no customers had logs configured to be pushed. The team quickly noticed the mistake and reverted the change in under five minutes.
Unfortunately, this first mistake triggered a second, latent bug in Logfwdr itself. A failsafe introduced in the early days of this feature, when traffic was much lower, was configured to “fail open”. This failsafe was designed to protect against a situation when this specific Logfwdr configuration was unavailable (as in this case) by transmitting events for all customers instead of just those who had configured a Logpush job. This was intended to prevent the loss of logs at the expense of sending more logs than strictly necessary when individual hosts were prevented from getting the configuration due to intermittent networking errors, for example.
When this failsafe was first introduced, the potential list of customers was smaller than it is today. This small window of less than five minutes resulted in a massive spike in the number of customers whose logs were sent by Logfwdr.
Even given this massive overload, our systems would have continued to send logs if not for one additional problem. Remember that Buftee creates a separate buffer for each customer with their logs to be pushed. When Logfwdr began to send event logs for all customers, Buftee began to create buffers for each one as those logs arrived, and each buffer requires resources as well as the bookkeeping to maintain them. This massive increase, resulting in roughly 40 times more buffers, is not something we’ve provisioned Buftee clusters to handle. In the lead-up to impact, Buftee was managing 40 million buffers globally, as shown in the figure below.

A short temporary misconfiguration lasting just five minutes created a massive overload that took us several hours to fix and recover from. Because our backstops were not properly configured, the underlying systems became so overloaded that we could not interact with them normally. A full reset and restart was required.
The bug in the Logfwdr configuration system was easy to fix, but it’s the type of bug that was likely to happen at some point. We had planned for it by designing the original “fail open” behavior. However, we neglected to regularly test that the broader system was capable of handling a fail open event.
The bigger failure was that Buftee became unresponsive. Buftee’s purpose is to be a safeguard against bugs like this one. A huge increase in the number of buffers is a failure mode that we had predicted, and had put mechanisms in Buftee to prevent this failure from cascading. Our failure in this case was that we had not configured these mechanisms. Had they been configured correctly, Buftee would not have been overwhelmed.
It’s like having a seatbelt in a car, yet not fastening it. The seatbelt is there to protect you in case of an accident but if you don’t actually buckle it up, it’s not going to do its job when you need it. Similarly, while we had the safeguard of Buftee in place, we hadn’t ‘buckled it up’ by configuring the necessary settings. We’re very sorry this happened and are taking steps to prevent a recurrence as described below.
We’re creating alerts to ensure that these particular misconfigurations will be impossible to miss, and we are also addressing the specific bug and the associated tests that triggered this incident.
Just as importantly, we accept that mistakes and misconfigurations are inevitable. All our systems at Cloudflare need to respond to these predictably and gracefully. Currently, we conduct regular “cut tests” to ensure that these systems will cope with the loss of a datacenter or a network failure. In the future, we’ll also conduct regular “overload tests” to simulate the kind of cascade which happened in this incident to ensure that our production systems will handle them gracefully.
Logpush is a robust and flexible platform for customers who need to integrate their own logging and monitoring systems with Cloudflare. Different Logpush jobs can be deployed to support multiple destinations or, with filtering, multiple subsets of logs.
Firefox version 133.0 is now available
Post Syndicated from jzb original https://lwn.net/Articles/999767/
Mozilla has announced
the release of Firefox 133.0. Notable in this release is the addition
of a new anti-tracking feature, Bounce Tracking Protection, which
detects trackers based on redirect
behavior and automatically purges their cookies and site data to
thwart tracking. The release also includes various
security fixes and more.
How SmugMug Increased Data Modeling Productivity with Amazon Q Developer
Post Syndicated from Will Matos original https://aws.amazon.com/blogs/devops/how-smugmug-increased-data-modeling-productivity-with-amazon-q-developer/
This post is co-written with Dr. Geoff Ryder, Manager, at SmugMug.
Introduction
SmugMug operates two very large online photo platforms: SmugMug and Flickr. These platforms enable more than 100 million customers to safely store, search, share, and sell tens of billions of photos every day. However, the data science and engineering team at SmugMug and Flickr often faces complex data modeling challenges that require significant time to resolve.
These challenges arise due to several factors. First, the team has to contend with diverse datasets from different sources. Additionally, the database schema and tables are highly complex, and the team needs to quickly understand application (PHP) code and database table structures in order to generate the necessary complex database queries. Specifically, SmugMug uses Amazon Redshift as its cloud data warehouse to analyze patterns in petabyte-scale data stored in Amazon S3, as well as transactional data in Amazon Aurora and Amazon DynamoDB. This allows them to generate dozens of business reports daily.
However, the complexity increases further as many database tables also need to be imported from third-party organizations into Amazon Redshift, where they are joined with SmugMug and Flickr’s internal tables. In extreme cases, properly modeling all these database tables and handling issues like granularity, cardinality, timestamps and missing data could take years – an impractical timeline for the business. We are excited to walk through SmugMug’s data modeling use cases and how SmugMug uses Amazon Q Developer to improve the data science and engineering team’s productivity.
Discovering Amazon Q Developer
SmugMug was one of the first customers to pilot Amazon Q Developer (previously Amazon CodeWhisperer), the most capable AI-powered assistant for software development that re-imagines the experience across the entire software development lifecycle, making it easier and faster to build, secure, manage, optimize, operate, and transform applications on AWS. There are multiple Amazon Q Developer use cases at SmugMug and Flickr, such as using Amazon Q Developer agent (/dev) for software development (i.e. generating implementation plans and the accompanying code), generating inline code suggestions, asking Amazon Q Developer in chat about AWS services and best practices, and analyzing AWS usage and costs for Cloud Financial Management (CFM) needs. For the data science and engineering team specifically, the key feature is chatting with Amazon Q Developer in integrated development environments (IDEs) like Intellij DataGrip. The data analysts and data scientists at SmugMug and Flickr ask questions in Amazon Q Developer chat to analyze database schemas, generate data model diagrams from DDL (Data Definition Language) statements, convert queries between languages, automatically generate complex database queries for data analysis, generate code to validate table contents, and predict trends using ML (Machine Learning).
Implementing Amazon Q Developer
To solve the data modeling challenges SmugMug faced, the team collaborated closely with their AWS Account Team, AWS Professional Services, and the Amazon Q Developer service team to create and test a data modeling assistant solution using Amazon Q Developer.
As a first step, the data modeler needs to bring the right metadata to bear. For simpler cases, the commands “show view myschema.v” or “show table myschema.t“ retrieve DDL schema information about the specified view or table from Amazon Redshift into the IDE console.
Here’s an example using simulated data for a hypothetical company. For this typical company that handles orders for products, the result of typing “show table sample.orderinfo” and “show table sample.skuinfo”might be:


This DDL text is now in the open tab. By selecting the text to highlight it, that DDL text becomes part of the context that Amazon Q Developer sees. The modeler can start asking questions about them in the Amazon Q Developer chat window in the IDE.

In complex scenarios, establishing the correct modeling context requires a combination of schema information, legacy SQL, application source code in various programming languages, sample values, and natural language documentation. Amazon Q Developer addresses this by creating a local index of relevant files and content. When a question is asked using @workspace, this index is consulted to identify and include pertinent sections of code and information in the request. (See this article for additional details on workspace). The prompt plays a crucial role in measuring similarity, so providing comprehensive context within it is essential. To optimize this process, the IDE settings feature a tunable workspace index function, allowing for enhanced performance in identifying and incorporating relevant context.
Workspace Index Settings
By adopting Amazon Q Developer as a team, we are able to jointly develop and share proprietary prompt text to address the four steps in our modeling process, as follows.
Step 1. Define the goal for the data modeling project
From prior knowledge, sketch a high-level goal for a data model. Gather the data for it manually, or by e.g. querying a vector database and adding its documents to the project.
For this example, we choose as the goal to compute aggregated metrics from a new table or view composed of two existing tables, sample.orderinfo and sample.skuinfo. These contain simulated data about product sales that are common to many companies. The order table is in the style of a fact table that logs customer orders, and the stock keeping unit (SKU) table is a dimension table that provides additional data points of interest about each order. The order and SKU information need to be combined by a join operation before we can compute the metrics. We would like Amazon Q Developer to tell us how to write that SQL join statement.
Step 2. Conduct an exploratory analysis and generate candidates
Next, prompt Amazon Q Developer for candidate foreign keys to join the tables, and for SQL code to execute those joins. Generate an entity-relationship diagram (ERD) as a visual aid. Prompts do not have to be complicated. For example:
@workspace What columns of database tables sample.orderinfo and sample.skuinfo would be best to join the two tables? Provide SQL code for the join. Draw an entity relationship diagram that shows the joins between the two tables, and includes only the fields involved in the join. Add a crow's foot cardinality marker to indicate a 1:many relationship, and add it next to the high cardinality table.


Each time tables are joined together, new aggregated metrics become available to drive business insights. Now, for instance, we can find the top selling SKUs in October thanks to our results:

Sometimes we need to look at code written in languages other than SQL to complete the data model. For example, the names of some vendors this company works with happen to appear in application PHP code as human readable strings, but are saved in the application database as numbers. The analytics data staged in Redshift only contain the numbers. So, we pull a copy of the PHP text file into @workspace, and ask Amazon Q Developer to translate the relevant string-integer mappings into a SQL case statement.
PHP Switch statement showing the mapping of Vendor Ids to String Names.
I am a Redshift database administrator and I am working on a data modeling problem. I would like to write SQL statements to join tables sample.orderinfo and sample.skuinfo. Please write that SQL to join the two tables. Also, I would like to write a SQL case statement to recover all string values defined in PHP that are represented as integer values in the database table.
The output of that prompt is shown below.

Amazon Q Developer automatically detected the PHP switch case statement, converted to SQL, and added it to the final query. Many other programming languages are supported, and modelers should try this technique with other kinds of source code. Note that data scientists and analysts may not know where to look in complex application code for these details, so this discovery-plus-code translation step is a net new benefit to our company that is only possible thanks to Amazon Q Developer.
Step 3. Create code to test the analysis
Now we request SQL source code for a battery of small test queries. These can return cardinality, grain, arithmetic, and null count results.
Please write a short SQL test to compute counts of the key fields that are used in the joins, which will verify the cardinality assignments indicated in the entity relationship diagram above. The SQL test should compare distinct counts to total counts and null counts when it verifies the cardinality.

Step 4. Validate the results of the analysis
Run the test queries to see if the candidate solution from step 2 meets our goals. The “Insert at cursor” button at the bottom of the response is handy for this. The data modeler can easily spot an error in the join logic and ERD from inspecting the output of the test query. (Or, if it’s hard to interpret the results, keep making the test queries simpler.) If errors arise from the AI misinterpreting or miscalculating a result, or from a vaguely worded prompt, simply adjust the prompt in step 2 to fix the known errors, and repeat steps 2 – 4.

After a few iterations, taking from seconds to at most tens of minutes each, the modeling errors have been worked out and we arrive at a valid production query.
Key Benefits and Results
With this Amazon Q Developer powered solution and iterative approach, SmugMug has achieved highly accurate data modeling results across numerous database tables. Once the correct modeling configuration is established, various useful outputs may become available.
We already described production SQL, unit tests, and ERDs for documentation. By the end of the process, because Amazon Q Developer has a good understanding of the data it just modeled in its chat history, it will also generate useful Python machine learning programs to predict business trends. Here is a prompt for that, and a partial screenshot of the Python output:
Please write Python code to implement a linear regression that predicts the quantity_ordered value based on other fields in the data set. Choose predictor variables that are less likely to cause multi-collinearity problems.

This only shows the model training step, but the full response included all library imports, a Redshift query, feature engineering steps, ML performance metrics, and code for plotting the metrics. And the AI can produce other types of predictive models. For example, you can try:
Please write Python code to implement an XGBoost model that predicts the quantity_ordered value based on other fields in the data set.
Ultimately, the solution has improved team productivity for both existing and new team members, while maintaining legacy knowledge needed to onboard new team members more efficiently. Key benefits include:
- Reducing SmugMug data analyst and scientist’s time spent on data modeling tasks from days to hours, allowing them to reallocate this time to other high-priority projects.
- Automating the generation of BI documentation and predictive ML, also saving crucial time.
- Providing net new value by translating application code constant definitions into SQL. Due to organizational boundaries, we would not have achieved this without an assist from the AI.
Future Plans and Expansion
SmugMug conducted the initial data modeling use case testing with over a dozen data science team members and analysts. We are moving on to analyze more complex tables and data schemas, and generating Python code in Amazon SageMaker for ML tasks like data preparation, training, inference, and MLOps. From our experience, Amazon Q Developer has become a preferred internal tool for development that has a data modeling component, and its use continues to expand to different groups around the company.
For SmugMug’s data modeling projects, we continue to enhance the four-step process described above. In order to gather the most relevant context to solve a problem, we build vector database collections to pull from schemas, older SQL code, application source code, BI tool content, and curated documentation. The vector search operation surfaces the right content, and spares data modelers from manually searching in different code archives. We use ChromaDB to do the searches, and bring the results from ChromaDB into the workspace as additional files.
Conclusion
Using Amazon Q Developer for data modeling use cases, SmugMug has managed to increase data science and engineering team productivity by up to 100% when compared to prior workflows. To explore how Amazon Q Developer can benefit your organization, get started here. If you have questions or suggestions, please leave a comment below.
About the Authors
Home Assistant 2024.12 Release Party
Post Syndicated from Home Assistant original https://www.youtube.com/watch?v=9Y9YY_YHNBY
Security updates for Tuesday
Post Syndicated from corbet original https://lwn.net/Articles/999744/
Security updates have been issued by Debian (pypy3), Fedora (chromium, cobbler, and libsoup3), Oracle (kernel), SUSE (glib2, govulncheck-vulndb, javapackages-tools, xmlgraphics-batik, xmlgraphics- commons, xmlgraphics-fop, libblkid-devel, opentofu, php8, postgresql, postgresql16, postgresql17, thunderbird, traefik, and ucode-intel), and Ubuntu (needrestart and rapidjson).
Cleaning hurricane damaged Retro Oddities, Modern Tech
Post Syndicated from LGR original https://www.youtube.com/watch?v=YbytSY4dIjA
Open Source: The Option for a Connected and Collaborative World
Post Syndicated from Luciano Alves original https://blog.zabbix.com/open-source-the-option-for-a-connected-and-collaborative-world/29237/
In my previous article, where we explored the TCO and ROI of open-source software, I raised topics that sparked substantive discussions, new research, and renewed insights. It is undeniable that we live in an era where collaboration and connectivity go beyond trends. They represent the foundation of current technology, especially in a world based on APIs.
In this context, open-source software stands out and positions itself as a logical and natural choice for companies and organizations (both public and private) that seek innovation, flexibility, security, and agility. Over the last two decades, the technology sector has validated this direction. Recently, the Open Source Program Office (OSPO) appeared in Gartner’s Hype Cycle for Emerging Technologies report, reinforcing its relevance and emerging as a maturing trend within 2 to 5 years.
Open Source in Gartner’s Hype Cycle
Gartner’s Hype Cycle for Emerging Technologies is a well-known tool for illustrating the phases of maturity, adoption, and impact of new technologies. In the current cycle, the Open Source Program Office (OSPO) appears as an emerging technology with the potential for corporate transformation in the coming years.
This highlights that it is not only a viable alternative to proprietary software, but an engine of innovation within organizations. The OSPO is, essentially, an internal structure in companies dedicated to promoting and managing the use of open-source software, ensuring compliance and governance.
With the strengthening of these structures, organizations not only maximize the benefits of open source but also foster a culture of continuous innovation and active collaboration with communities, whether through service contracts, participation in working groups, or even funding new functionalities.
A Natural Strategic Choice
Experience shows that open source is a strategic path for organizations aiming to thrive in an increasingly interconnected and competitive market. The transparency, flexibility, and scalability offered by such solutions surpass the limitations of proprietary solutions, facilitating a more adaptable and agile adoption.
Additionally, the collaborative approach of this model aligns with today’s reality, where knowledge sharing and co-creation are essential for technological development within organizations. Companies like Google, Microsoft, and Red Hat have already recognized this reality and invest in their own Open Source Program Offices. These initiatives not only underline the commitment to open innovation but also highlight tangible benefits in terms of efficiency, cost reduction, and speed in the development of innovations.
The Future is Open Source
The inclusion of OSPO in Gartner’s Hype Cycle indicates that companies that have not yet embarked on this journey need to reconsider their strategies. In an environment where constant adaptation and innovation are essential for growth and efficiency, open source has ceased to be optional and has become a necessity. As adoption expands across various sectors and applications, companies that build a solid framework for evaluating and maximizing the benefits of these technologies will be in a privileged position to lead their markets.
At Zabbix, we understand the importance of open source not just as a technological solution, but as a philosophy aimed at democratizing technology, fostering continuous innovation, and cultivating a culture of collaboration—a vision that OSPOs have been solidifying in companies across multiple industries. The discussion about the Total Cost of Ownership (TCO) and Return on Investment (ROI) in open-source solutions is just the starting point.
Tools like Zabbix prove that this is an effective strategy for monitoring and maintaining critical environments. Open source is, and will continue to be, the driving force behind the innovations that will transform the way companies sustain their businesses and interact with customers and users. The future is already open source, and the time to embrace this transformation is now.
The post Open Source: The Option for a Connected and Collaborative World appeared first on Zabbix Blog.
What Graykey Can and Can’t Unlock
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/11/what-graykey-can-and-cant-unlock.html
This is from 404 Media:
The Graykey, a phone unlocking and forensics tool that is used by law enforcement around the world, is only able to retrieve partial data from all modern iPhones that run iOS 18 or iOS 18.0.1, which are two recently released versions of Apple’s mobile operating system, according to documents describing the tool’s capabilities in granular detail obtained by 404 Media. The documents do not appear to contain information about what Graykey can access from the public release of iOS 18.1, which was released on October 28.
More information:
Meanwhile, Graykey’s performance with Android phones varies, largely due to the diversity of devices and manufacturers. On Google’s Pixel lineup, Graykey can only partially access data from the latest Pixel 9 when in an “After First Unlock” (AFU) state—where the phone has been unlocked at least once since being powered on.
Is Ambivalence Killing Parenthood?
Post Syndicated from The Atlantic original https://www.youtube.com/watch?v=qBZ9wjHwimY
Особеностите на българския консерватизъм
Post Syndicated from original https://www.toest.bg/osobenostite-na-bulgarskiya-konservatizum/
Аз съм леберал, от лебералната партия (…) Абе, бай Иречек, я ми кажи твоя милост леберал ли си, консерватор ли си? Май-май, че си консерва, както виждам.

Из „Бай Ганьо“ от Алеко Константинов
Признавам си, че от малък изпитвам силни симпатии към консерватизма и вината за това донякъде е на горния цитат от Алеко Константинов, който наред със семейната среда създаде превратна представа за идеологията в още юношеската ми психика – на добре възпитани, добре образовани, тихи хора, мъчещи се да донесат просвещението сред широките простонародни маси. По-късно през живота си оцених вече на рационално ниво ползата от консервативното мислене, понякога служещо като сито на здравия разум срещу някои по-дръзки и невъздържани идеи, макар на емоционално ниво да се дразнех от постоянното поклащане с пръст към едно или друго.
За съжаление обаче, в последните години забелязах, че в разговора, който водим за консерватизма, съдържанието на понятието се измени драстично и семиотичното му значение отскочи от Константин Иречек към Бай Ганьо. Започна да се приема за аксиома, че българите са консервативен народ, като това се изразява в привързаността към техните традиции и в отхвърлянето на новото, а изискванията за прилично поведение и интелектуална подготовка някак отпаднаха като демоде, едва ли не като либерални, да не кажа джендърски. (Някой сполучливо беше написал във Facebook, че у нас добрите обноски вече са толкова редки, че жените ги възприемат като флирт, а мъжете – за проява на хомосексуалност.)
Разбира се, нормално е значението на думите да се променя с времето, като най-болезненият за мен пример е с думата експертиза, която от оценка от специалист започна да става синоним на компетентност, не без усилията и на Бойко Борисов, вероятно използвал думата, подведен от значението ѝ в английския език. Затова ми се ще да разгледам какво точно представлява българският консерватизъм, дали наистина нашенци са чак толкова привързани към тази, общо взето, строга и изискваща доктрина, или отново говорим някак наизуст, „алангро“, както веднъж изтърси Кирил Петков.
Кратка история на българския консерватизъм
Българските консерватори всъщност се появяват след Освобождението на България като политическа партия, която се отнася със скептицизъм към компетентността на още девствения откъм демократични порядки народ да се управлява напълно самостоятелно, и се опитва да ограничи силата му с различни предложения, повечето от които отхвърлени. Мисля, че е емблематичен примерът за красноречивата защита на Константин Стоилов за двукамарен парламент, посечена от Петко Р. Славейков, умело успял да ѝ се присмее със звучна българска пословица – ако не се лъжа за жабата, която видяла как подковават вола, и също подала крак. Това обрича консерваторите да са партия на малцинството, разчитаща на взаимодействие с княза, и донякъде затова доскоро бях останал с впечатлението, че е нормално хората с такива убеждения да се родеят по-скоро с образованото малцинство, а не с широките (просто)народни маси. Днес „инак е наредено“, ако мога отново да цитирам Алеко, но за това – след малко.
Българските партии доста се изменят в историята си до Девети септември, а след това са забранени от комунистите – злощастен край, който получава ново начало след Десети ноември. Но и тогава първоначално с консерватизма по-скоро свързвахме сякаш Демократическата партия на покойния Стефан Савов (иначе произхождаща исторически от либералите) и по-късно ДСБ на бившия премиер Иван Костов, която целенасочено търсеше прилика с британските тори и също толкова упорито си бе изградила имидж на сила, включваща знаещи и можещи хора над средното ниво, макар че така трудно се харесваха от избирателите.
Ситуацията започна да се променя с появата на политическа партия ГЕРБ, която, въпреки уверенията на Бойко Борисов, че е „центристко-дясна“, започна донякъде да се отъждествява с консерватизма. Спомням си, че навремето това провокира една наша журналистка да напише подигравателна статия как българските тори празнуват след победата си на избори с чалга. Оттам започна промяната на същностното разбиране що е то консерватизъм, като към него по-късно се присъединиха политически сили като „Ред, законност и справедливост“ на Яне Янев (мутирала от НС–БЗНС, на която Янев беше председател – наистина втрещяваща метаморфоза) и ВМРО на Красимир Каракачанов, харесала си „Европа на нациите“ на паметните европейски избори, когато се яви в коалиция с „България без цензура“ на Николай Бареков – още едно интересно решение, тъй като консерватизмът всъщност предполага известна цензура. Но млъкни, сърце!
Днес нещата са се видоизменили напълно и като консерватори се възприемат донякъде ГЕРБ и най-вече крайнодесните партии, като „Величие“, „Възраждане“ и МЕЧ, а понякога и Българската социалистическа партия, което вече действително е български принос към световната теория на политиката. Единственото изключение е партия КОД на Петър Москов, която изглежда старомодно консервативна, с високообразовани кадри и кандидати, но поради това и обречена на изключително мижав интерес от страна на избирателите. Понякога изглежда, че тя е урочасала сама себе си, целейки се в изключително тънката прослойка на интелигентни хомофоби – хора, за които не съм сигурен, че наистина съществуват. Неслучайно споменавам хомофобията, тъй като тя всъщност е основен аргумент за консерватизма на една или друга политическа ценност, наред с омразата към либералите. Тези неща обаче идват от Америка.
Либерали срещу консерватори, либерали и консерватори, либерали = консерватори?!
САЩ е страната, където либералите се отъждествяват с лявото и са съставна част на Демократическата партия, като се борят за правата на жените и различни маргинализирани групи – афроамериканци, испаноговорещи, ЛГБТ+. Консерваторите са главно в Републиканската партия и се отъждествяват с пазенето на традицията, защитата на семейните ценности и уповаването на християнската вяра за напътствия в политиката. Именно в тази страна съществува ожесточено противопоставяне между либерали и консерватори, което вдъхновява ситуацията и в други държави, например Южна Корея, където либералната и консервативната партия водят битка за властта и ожесточена културна война за и против феминизма, или пък Канада, където отново политически сили с тези две имена спорят за правото да управляват страната, макар всъщност идейно да не са чак толкова различни една от друга. Оттам сякаш се възприема и определението за либерали и консерватори у нас, но то дава дефекти, тъй като всъщност България не е част от тази политическа система.
В Европа под либерали се възприема друго – хора, които са за свобода в търговията и минимални регулации на държавата в икономиката, и това всъщност ги изпраща надясно. В редица държави тези партии са естествен съюзник на консерваторите в спора им със социалдемократите, заемащи ролята на левица в повечето страни на Стария континент. Либерали от този вид съществуват във Великобритания, в Германия, такава е и партията на Еманюел Макрон във Франция. В САЩ такива либерали биха били по-близки до малката партия на либертарианците – с уговорката, че в тази страна цялата политическа рамка е преместена доста по-надясно, макар и основно в икономически план. Оттам обаче идва любимият ми девиз на въпросния тип либерализъм – „вън от портфейла и вън от спалнята ви“.
Картината се усложнява допълнително от това, че в Австралия либералите са основна част от дясна коалиция и всъщност заемат ролята на консерватори, борещи се срещу левите лейбъристи. Управляващата в Япония консервативна партия „Джиминто“ също буквално се нарича Либералдемократическа партия. Впрочем това правеше и ултранационалистическата партия на Жириновски, макар последното да може да се определи по-скоро като куриоз.
В България либерална партия от европейски тип поне на хартия беше старото единно Движение за права и свободи, тъй като се предполагаше, че то се бори за права на малцинствата и за малко регулация в икономиката. Това го правеше естествен член на европейската либерална партия АЛДЕ, ако успеем да се абстрахираме от националните специфики на българската политическа почва (по Димитър Ганев), включваща обръчи от фирми и клиентелизъм. Наскоро партия „Продължаваме промяната“ потърси членство в „Обнови Европа“ – групата на АЛДЕ в Европейския парламент. Може да се каже, че предвид по-социалната политика на Асен Василев, донякъде е възможно да говорим за либерална партия от американски тип – с уговорката, че Кирил Петков се самоопредели като традиционалист по отношение на въпроси като гей браковете, поради което не трябва да бързаме с категоризацията. След решението си за членство в ЕНП Движение „Да, България“ е по-скоро в център-дясното пространство, а ДСБ си остават консерватори, макар и, изглежда, от по-умерения тип, характерен например за Канада. Последното оголва българския консерватизъм на националистите.
Колко точно сме консервативни българите
Един от споровете, предизвикал най-нажежени дискусии по оста либерално–консервативно през последните години, е за самоопределянето на транс хората в пол, различен от биологично зададения. В този ред на мисли е добре да се отбележи, че много хора у нас са само от консервативен джендър, без реално да са от това политическо семейство. Позволявам си тази оценка заради някои специфики на нашето общество, които следва да бъдат отбелязани.
На първо място, макар голям брой българи да се определят като православни, част от тях не вярват в Бога, а възприемат религията като белег на националното, нещо като духовна версия на кюфтетата по чирпански. Още по-малък е броят на хората, които редовно ходят на църква и споделят тайнството на евхаристията. Вместо това повечето българи са така наречените ВиК християни – посещават храма на Великден и Коледа, като, за съжаление, в случая с първия празник често се оставят следи от яйчени черупки, трохи от козунаци и дори пластмасови бутилки от бира в дворовете на църквите. Разбира се, аз не съм фанатик и приемам правото на всеки да вярва по свой начин, даже смятам, че в интуитивното познание за Твореца понякога има повече истина от суровите догми на едно или друго вероизповедание. Добре е обаче човек да има предвид, че ако просто смята как горе на небето „има нещо“, не е добре да се пише ревностен християнин и консерватор, тъй като се въвежда в самозаблуда.
На второ място, голям брой българи живеят в безбрачие или изобщо нямат връзка. Отново, това по никакъв начин не е упрек към хората. Живеем в XXI век, двама възрастни могат сами да преценят дали желаят да документират връзката си пред Църквата или държавата, решение на всеки е дали изобщо е създаден за моногамен живот. Отново обаче, малко ексцентрично е някой да се пъчи като заклет консерватор и в същото време да е стар ерген със слаб ангел или да живее щастливо без брак. За хората, които тайно са хомосексуални, но се пишат за консервативни и облъчват с хомофобия, няма да кажа нищо, само ще препоръчам филма „Американски прелести“ с Кевин Спейси – намирам го за доста поучителен.
На трето място, българите, ако наистина се считат за консерватори, трябва да се замислят за някои неща. У нас, според мен за щастие, абортите са легални и въпреки напъните на някои от идеолозите, торпилирали Истанбулската конвенция, не се очертава скоро да бъдат забранени. Хазартът процъфтява – хората редовно залагат на всевъзможни мачове, доскоро рекламите на различни компании от този отрасъл ни облъчваха ежечасно до степен, че на голямо първенство по футбол човек не можеше да види едно клипче за студена бира. Сега нещата са малко по-добре, но комарът все още остава опасно популярен. Както и чалгата – музика, която е доста разкрепостена като визия и послания, но се радва на любов от страна на населението, включително и от някои защитници на традиционните ценности. Ще се потретя: нека всеки слуша каквото си иска, но да се препоръчва после като строг консерватор е смехотворно.
Същината на така наречения консерватизъм
В действителност в бума на „консерватори“ у нас се коренят две неща, като едното донякъде произхожда от другото. Така нареченият ни консерватизъм всъщност си е чист национализъм, който не изисква абсолютно нищо от симпатизантите си като ниво, образование и възпитание, а просто им казва, че са по-добри от останалите заради това как са се родили – българи, хетеросексуални и православни. В резултат това ги учи да се противопоставят на всичко космополитно, което ни свързва с останалия свят – от съвременното кино до празници като Хелоуин, но също и на български творци като Господинов, получили признание навън, независимо от вкаменели нашенски институции, като Съюза на българските писатели.
Второто нещо е хомофобията, представена като защита на традиционните ценности. Приемането на различните и самите различни са представяни като пъклен план на Запада срещу българщина̀та. Но това всъщност е символ на променящия се свят, който националистите сякаш вярват, че могат да замразят във времето с престорения си консерватизъм. Това идва, естествено, от пропагандата на руснаците, дърпащи конците на много от така наречените български националисти и консерватори, и е част от плана им да ни засмучат обратно в техния руски свят на преклонение пред авторитарния вожд. Но първо, няма как да успее – освен ако не дойде с танковете на нов Девети септември, и второ, хората нямат идея колко е прекалено, погледнато отвън.
Защото българите са хомофоби не само в сравнение с калифорнийците или скандинавците, но дори с тексасците, поляците или жители на страни като Аржентина, където нивата на приемане са по-високи от българските, независимо от ширещата се бедност. Дори републиканците в САЩ по-скоро се фокусират върху специфични и поне според мен действително спорни практики, като участието на транс атлети в категории, съответстващи на техния джендър (а не биологичен пол), и Джей Ди Ванс, тогава все още кандидат, а не избран вицепрезидент, весело обяви преди изборите, че очаква да спечели подкрепата на „нормалните гейове“.
Ние обаче следваме руската хомофобия и руската идея за консерватизъм, дело на един политически елит, който по всяка вероятност сам не вярва на глупостите, които бръщолеви – поне ако съдим по това къде живеят и какво говорят децата му. Наскоро дъщерята на кремълския говорител Песков жизнерадостно съобщи от Париж, че подкрепя еднополовите бракове.
Kremlin 💩hole Dmitry Peskov's daughter lives in Paris and likes same-sex marriage. She loves to live in Paris, not Gulag 🇷🇺 pic.twitter.com/R5fQE058BO
— Beautiful Russia (@BeRuzzia) October 6, 2024
За сметка на това президентът Путин, лидер на глобалната версия на новия националконсерватизъм (последното звучи малко като Oбществото на плоската Земя, което имало симпатизанти по целия глобус), смята, че най-голямата геополитическа трагедия в историята е разпадът на СССР – страната, в която рушаха църкви, избиваха свещеници и подготвяха процеси срещу Бога.
Какво пък, на този фон омразата към Хелоуин изглежда направо безобидна.
XikeStor SKS8300-8X Review a Sub $90 8-port Managed 10G Switch
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The XikeStor SKS8300-8X is perhaps the cheapest 8-port 10G switch we could find at under $90 and it has console and web management
The post XikeStor SKS8300-8X Review a Sub $90 8-port Managed 10G Switch appeared first on ServeTheHome.
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