Forwarded from DevOps & SRE notes (tutunak)
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❤5
A cross-platform, fast and extensible general purpose fuzzy finder 📺
https://github.com/alexpasmantier/television
https://github.com/alexpasmantier/television
GitHub
GitHub - alexpasmantier/television: A very fast, portable and hackable fuzzy finder for the terminal.
A very fast, portable and hackable fuzzy finder for the terminal. - alexpasmantier/television
❤7
A guide by Rami McCarthy explains how to create AWS IAM service roles systematically—examining options like DSLs (e.g., policy_sentry), GUIs, and LLM‑based natural‑language tooling to address notoriously complex permission configurations
https://ramimac.me/iam-service-roles?ck_subscriber_id=2797503477
https://ramimac.me/iam-service-roles?ck_subscriber_id=2797503477
High Signal Security
Industrial IAM Service Role Creation
A guide to tools for creating AWS IAM service roles.
👍3❤1
A writeup by Maxim Onyshchenko shares insights into boosting Terraform efficiency—highlighting modular architecture, remote state management, CI/CD integration, and validation techniques to streamline infrastructure workflows
https://medium.com/@maximonyshchenko/the-secret-to-terraform-efficiency-a76140a5dfa1
https://medium.com/@maximonyshchenko/the-secret-to-terraform-efficiency-a76140a5dfa1
Medium
The secret to Terraformʼs efficiency
*This article is for Terraform heavy users, who manage complex infrastructures.
👍5❤1
Meshery Extensions are plugins or add-ons that enhance the functionality of the Meshery platform beyond its core capabilities.
https://github.com/meshery-extensions/helm-kanvas-snapshot
https://github.com/meshery-extensions/helm-kanvas-snapshot
GitHub
GitHub - meshery-extensions/helm-kanvas-snapshot
Contribute to meshery-extensions/helm-kanvas-snapshot development by creating an account on GitHub.
👍3
A blogpost by Ali Sattari delves into various methods for aggregating service-level indicators (SLIs) into single metrics—covering approaches like summing events, weighted averages, percentiles, and counting SLO compliance
https://ali.sattari.me/posts/2024/aggregating-slis/
https://ali.sattari.me/posts/2024/aggregating-slis/
ali.sattari.me
Aggregating SLIs
With a great number of SLIs come great responsibility aggregation issues. While aggregation provides more readability in overviews, it also inadvertently hides nuances and details. Our aim should be to propose a sensible aggregation method that ensures we…
👍2❤1
An article from Gremlin shares reliability recommendations for organizations adopting Kubernetes—urging teams to proactively test failure modes (e.g., simulate liveness probe failures, pod blackholes), learn from incidents, and implement resilience pipelines with tools like Gremlin's “Detected Risks” and reliability scorecards
https://www.gremlin.com/blog/reliability-recommendations-when-adopting-kubernetes
https://www.gremlin.com/blog/reliability-recommendations-when-adopting-kubernetes
Gremlin
Reliability recommendations when adopting Kubernetes
General reliability best practices when adopting Kubernetes.
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A writeup on DZone discusses maintaining alignment between two multi-master databases using a vector clock approach—employing asynchronous bi-directional message queues (via Kafka and Avro) and identical alignment algorithms on both sides
https://dzone.com/articles/keeping-two-multi-master-dbs-aligned-with-vector-clock
https://dzone.com/articles/keeping-two-multi-master-dbs-aligned-with-vector-clock
DZone
Keeping Two Multi-Master Databases Aligned With a Vector Clock
In this article, learn about an experience in keeping two different databases aligned with two different technologies by using an application-level solution.
A post by Yorick Peterse provocatively argues that asynchronous I/O—despite its efficiency gains—may be the “next billion‑dollar mistake,” tracing its complexities in both programming models (cooperative vs preemptive) and runtime implementations
https://yorickpeterse.com/articles/asynchronous-io-the-next-billion-dollar-mistake/
https://yorickpeterse.com/articles/asynchronous-io-the-next-billion-dollar-mistake/
👍2
A guide by Eric Carter unveils how Sysdig’s AI Workload Security for AWS can automatically detect usage of Amazon Bedrock, SageMaker, and Q—identifying real-time risks like unauthorized access, data tampering, and public exposure
https://sysdig.com/blog/ai-workload-security-for-aws/?ck_subscriber_id=2797503477
https://sysdig.com/blog/ai-workload-security-for-aws/?ck_subscriber_id=2797503477
👍2
A blogpost by Rami McCarthy and Daniel Grzelak humorously critiques AWS's inconsistent deletion patterns, highlighting how various services employ different confirmation mechanisms—ranging from typing “delete” to scheduling deletions. They explore how these inconsistencies can lead to accidental deletions and suggest that AWS could benefit from a more standardized approach .
https://awssecuritydigest.com/articles/eleventeen-ways-to-delete-an-aws-resource?ck_subscriber_id=2797503477
https://awssecuritydigest.com/articles/eleventeen-ways-to-delete-an-aws-resource?ck_subscriber_id=2797503477
Awssecuritydigest
Eleventeen ways to delete an AWS resource
Deleting stuff in AWS brings us great joy. Lucky there are infinite ways to do it!
❤6
KevisAlex’s “Interpreting Terraform Plan Outputs with the Help of an LLM” demystifies how large language models can translate Terraform’s complex plan data into practical insights. This blogpost guides DevOps teams through clear, step-by-step examples to streamline infrastructure as code workflows.
https://medium.com/@KevsAlex/interpreting-terraform-plan-outputs-with-the-help-of-an-llm-8f9824c63ecd
https://medium.com/@KevsAlex/interpreting-terraform-plan-outputs-with-the-help-of-an-llm-8f9824c63ecd
Medium
Interpreting Terraform Plan Outputs with the Help of an LLM
So, you’ve got a Terraform plan output in front of you. It’s filled with lines of code that look like a language only your computer…
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