The article "Linux LKM Persistence" explores advanced techniques for maintaining persistence on Linux systems using loadable kernel modules (LKMs). It delves into the methods of loading malicious kernel modules at boot time, focusing on the use of the
https://righteousit.com/2024/11/18/linux-lkm-persistence/
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systemd-modules-load service to install and hide a rootkithttps://righteousit.com/2024/11/18/linux-lkm-persistence/
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Righteous IT
Linux LKM Persistence
Some thoughts on how to persist your Linux LKM rootkits and some ideas for detection.
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The article "Using Tracetest with OpenTelemetry for Trace-based Testing" explores the concept of trace-based testing in distributed systems and introduces tools to implement this approach. It delves into the basics of distributed tracing, compares it with traditional logging methods, and demonstrates how to use OpenTelemetry for instrumentation and Tracetest for creating and running trace-based tests.
https://tracetest.io/blog/trace-based-testing-with-opentelemetry-using-tracetest-with-opentelemetry
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https://tracetest.io/blog/trace-based-testing-with-opentelemetry-using-tracetest-with-opentelemetry
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tracetest.io
Trace-based Testing with Tracetest + OpenTelemetry | Tracetest Blog
Learn the basics of distributed tracing, the differences between tracing and logging, an intro to OpenTelemetry (a set of observability tools), and an intro to Tracetest for trace-based testing.
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A Helm plugin that uses Common Expression Language (CEL) to validate values. Instead of using JSON Schema in values.schema.json, you can write more expressive validation rules using CEL in values.cel.yaml.
https://github.com/idsulik/helm-cel
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https://github.com/idsulik/helm-cel
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GitHub
GitHub - idsulik/helm-cel: A Helm plugin that uses Common Expression Language (CEL) to validate values. Instead of using JSON Schema…
A Helm plugin that uses Common Expression Language (CEL) to validate values. Instead of using JSON Schema in values.schema.json, you can write more expressive validation rules using CEL in values.c...
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Kyanos is an ebpf based networking analysis tool. It can visualize the time packets spend in the kernel, analyze requests/responses in command line, suppport various L7 protocols like HTTP/Redis/MySQL.
https://github.com/hengyoush/kyanos
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https://github.com/hengyoush/kyanos
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GitHub
GitHub - hengyoush/kyanos: Kyanos is a networking analysis tool using eBPF. It can visualize the time packets spend in the kernel…
Kyanos is a networking analysis tool using eBPF. It can visualize the time packets spend in the kernel, capture requests/responses, makes troubleshooting more efficient. - hengyoush/kyanos
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The article details Timescale's journey to optimize upsert performance on compressed hypertables in TimescaleDB, a PostgreSQL extension. It describes how the team addressed a customer's challenge with suboptimal upsert performance, ultimately achieving a 300x speed improvement by leveraging existing indexes for efficient conflict resolution during upserts on high-cardinality datasets.
https://www.timescale.com/blog/how-we-made-postgresql-upserts-300x-faster-on-compressed-data
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https://www.timescale.com/blog/how-we-made-postgresql-upserts-300x-faster-on-compressed-data
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TigerData Blog
How We Made Postgres Upserts 300x Faster on Compressed Data
Read how we made upsert performance 300x faster on compressed data by moving from PostgreSQL sequential scans to index scans.
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The article discusses setting up a self-hosted full-stack observability system for startups using open-source tools, emphasizing the importance of monitoring system performance as businesses scale. It outlines key components and tools like OpenTelemetry, OpenSearch, Prometheus, and Grafana to achieve comprehensive system visibility without incurring high SaaS costs
https://osuite.io/articles/full-stack-observability-self-hosted
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https://osuite.io/articles/full-stack-observability-self-hosted
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osuite.io
Self hosting full stack observability
This article showcases the architecture of a cost-effective observability system using open-source tools, enabling startups to monitor their systems effectively without incurring high SaaS costs.
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☁️ AWS Morning Brief – AWS News with a Twist ☁️
Stay updated on the latest AWS news—sprinkled with snark! With over 60+ AWS posts daily, we cut through the noise to bring you the hidden gems, top community contributions, and the must-know updates**—all summarized with **wit and clarity.
🔍 Curated AWS News & Insights
🎙 No-Nonsense, Snarky Summaries
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✨ Subscribe now and get your AWS updates—minus the nonsense! 📲
Stay updated on the latest AWS news—sprinkled with snark! With over 60+ AWS posts daily, we cut through the noise to bring you the hidden gems, top community contributions, and the must-know updates**—all summarized with **wit and clarity.
🔍 Curated AWS News & Insights
🎙 No-Nonsense, Snarky Summaries
🚀 Stay Informed Without the Overload
✨ Subscribe now and get your AWS updates—minus the nonsense! 📲
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Bare metal to production ready in mins; your own fly server on your VPS.
https://github.com/MightyMoud/sidekick
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https://github.com/MightyMoud/sidekick
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GitHub
GitHub - MightyMoud/sidekick: Bare metal to production ready in mins; your own fly server on your VPS.
Bare metal to production ready in mins; your own fly server on your VPS. - MightyMoud/sidekick
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The authro explores the emerging trend of AI agents in the observability and monitoring space, discussing how these agents could potentially revolutionize the way operational data is processed and utilized. It highlights various startups developing AI-powered solutions for DevOps, incident response, and SRE tasks, while also addressing potential challenges such as data privacy concerns and the need for benchmarking to evaluate agent effectiveness.
https://monitoring2.substack.com/p/ai-agents-invade-observability
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https://monitoring2.substack.com/p/ai-agents-invade-observability
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Substack
AI agents invade observability: snake oil or the future of SRE?
The Mooster and friends would like to join your ops team: understanding what happens when generative AI agents meet observability and monitoring software.
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List of changes announced for AWS that may break existing code
https://github.com/SummitRoute/aws_breaking_changes
https://github.com/SummitRoute/aws_breaking_changes
GitHub
GitHub - SummitRoute/aws_breaking_changes: List of changes announced for AWS that may break existing code
List of changes announced for AWS that may break existing code - SummitRoute/aws_breaking_changes
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The article compares the performance characteristics of Classic and Quorum queues in RabbitMQ, highlighting their strengths and use cases. It presents benchmark results showing that Classic queues offer higher throughput and lower latency, making them suitable for high-performance applications, while Quorum queues provide better fault tolerance and durability at the cost of reduced performance, making them ideal for mission-critical systems requiring high availabilitys
https://dzone.com/articles/battle-of-the-rabbitmq-queues-performance-insights
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https://dzone.com/articles/battle-of-the-rabbitmq-queues-performance-insights
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DZone
Battle of the RabbitMQ Queues: Performance Insights on Classic and Quorum
When deciding between RabbitMQ’s Classic and Quorum queues, it’s important to recognize that both have their strengths and weaknesses. Learn more here.
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🐸 a database management tui for postgres
https://github.com/achristmascarl/rainfrog
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https://github.com/achristmascarl/rainfrog
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GitHub
GitHub - achristmascarl/rainfrog: 🐸 a database tool for the terminal
🐸 a database tool for the terminal. Contribute to achristmascarl/rainfrog development by creating an account on GitHub.
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Slack's engineering team details their journey in evolving their Chef infrastructure to manage tens of thousands of EC2 instances efficiently. The article explores the challenges faced and solutions implemented as they transitioned from a single Chef stack to a sharded infrastructure, improving reliability and deployment safety for their vast and growing infrastructure.
https://slack.engineering/advancing-our-chef-infrastructure/
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https://slack.engineering/advancing-our-chef-infrastructure/
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Engineering at Slack
Advancing Our Chef Infrastructure - Engineering at Slack
At Slack, we manage tens of thousands of EC2 instances that host a variety of services, including our Vitess databases, Kubernetes workers, and various components of the Slack application. The majority of these instances run on some version of Ubuntu, while…
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The blogpost discusses the creation of SREBench, a Kubernetes task dataset designed to evaluate LLM performance in root cause analysis of Kubernetes issues. It details the challenges faced by the Parity team in developing a reliable benchmark for their AI agent, ultimately leading to the creation of a synthetic dataset inspired by the MuSR murder mystery reasoning benchmark
https://www.tryparity.com/blog/how-and-why-we-made-srebench-swebench-for-k8s
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https://www.tryparity.com/blog/how-and-why-we-made-srebench-swebench-for-k8s
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Tryparity
How and Why We Made SREBench, SWEBench for Kubernetes - Parity
How and Why We Made SREBench, SWEBench for Kubernetes - We made SREBench, a k8s task dataset, to evalute LLM performance on root causing kubernetes issues
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Open source ngrok alternative designed for teams. Tunnel http, tcp or websocket connections.
https://github.com/amalshaji/portr
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https://github.com/amalshaji/portr
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GitHub
GitHub - amalshaji/portr: Expose local http, tcp or websocket connections to the public internet
Expose local http, tcp or websocket connections to the public internet - amalshaji/portr
Workspace and session management TUI for terminal environments
https://github.com/GianlucaP106/mynav
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https://github.com/GianlucaP106/mynav
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GitHub
GitHub - GianlucaP106/mynav: Workspace and session management TUI
Workspace and session management TUI. Contribute to GianlucaP106/mynav development by creating an account on GitHub.
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Discord embarked on a six-month project to reduce bandwidth usage for their clients, particularly on iOS and Android, aiming to create a more responsive experience. The initiative focused on improving the "gateway" service, which provides real-time updates to clients, by transitioning from zlib compression to zstandard, which offers higher compression ratios, faster compression times, and support for dictionaries[
https://discord.com/blog/how-discord-reduced-websocket-traffic-by-40-percent
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https://discord.com/blog/how-discord-reduced-websocket-traffic-by-40-percent
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Discord
How Discord Reduced Websocket Traffic by 40%
How we rolled out zstandard and other improvements across our gateway cluster to reduce the amount of bandwidth that’s used by our clients.
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☁️ Screaming in the Cloud – Cloud Computing with a Twist ☁️
Join Corey Quinn as he dives into unfiltered conversations with domain experts across the cloud industry. From AWS, GCP, and Azure to Oracle Cloud, this podcast unpacks the "why" behind cloud decisions**—with a dose of humor and critical insight.
🎙 **Expert Talks on Cloud & DevOps
☁️ AWS, GCP, Azure & Beyond
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✨ Subscribe now and stay ahead in the ever-evolving cloud landscape! 📲
Join Corey Quinn as he dives into unfiltered conversations with domain experts across the cloud industry. From AWS, GCP, and Azure to Oracle Cloud, this podcast unpacks the "why" behind cloud decisions**—with a dose of humor and critical insight.
🎙 **Expert Talks on Cloud & DevOps
☁️ AWS, GCP, Azure & Beyond
🔥 Sharp Insights with a Side of Snark
✨ Subscribe now and stay ahead in the ever-evolving cloud landscape! 📲
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The article discusses a critical incident involving Postgres indexing at a high-volume database with billions of rows. It highlights the potential pitfalls of concurrent indexing, which can fail silently and lead to performance issues. The author shares best practices for Postgres indexing, including using the CONCURRENTLY flag, monitoring index creation, validating indexes manually, and properly handling partitioned tables.
https://blog.bemi.io/indexing/
https://blog.bemi.io/indexing/
Bemi AI Blog
When Postgres Indexing Went Wrong
It’s important to understand basics of indexing and best practices around them for preventing system downtime.
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