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

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

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

Kafka TUI client

https://github.com/jonas-grgt/ktea

Migrate to PostgreSQL in a single command!

https://github.com/dimitri/pgloader

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/

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

Terminal JSON viewer & processor

https://github.com/antonmedv/fx

The SQL IDE for Your Terminal.

https://github.com/tconbeer/harlequin

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

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/

Meshery, the cloud native manager

https://github.com/meshery/meshery

AI powered Kubernetes Assistant

https://github.com/GoogleCloudPlatform/kubectl-ai

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

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

kro | Kube Resource Orchestrator

https://github.com/kro-run/kro

Command line csv viewer

https://github.com/YS-L/csvlens

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

Recently, I received a message from a recruiter about an open position. We chatted, I sent my CV, and after a week they asked about my desired salary. Then they set a time to sign an NDA before any interview. That was my first warning sign.
I read the NDA carefully and found a few red flags worth sharing (my personal view, not legal advice):

Very broad definition of “Confidential Information.”
The NDA says “Confidential Information” means “any and all information…in whatever form,” including “business plans, forecasts, projections, analyses, compilations, records and other materials” . This could cover even simple chat notes - so you might break the agreement just by asking a normal question.

Three‑year term.
The NDA stays in force for three years from signing . For a one‑time interview, this long period seems too much. It could stop you from working on similar projects elsewhere for a long time.

Foreign jurisdiction.
All disputes must go to the DIFC Courts in Dubai under DIFC law . If you disagree, you could face high travel and legal costs to defend yourself there.

No warranties on information.
The NDA states there are no promises about the accuracy or completeness of the shared information . Yet if you accidentally misuse something, you are fully responsible.

Surprise timing of the NDA.
The recruiter never mentioned the NDA at the start. It only appeared at a late stage - after salary discussions and interview timing agreement. That “tricky” timing feels like a hidden catch.

Always read an NDA line by line. Ask:
- “What exactly counts as confidential?”
- “Why is the term so long?”
- “Am I okay with this jurisdiction?”
A few clear questions now can save you big headaches later.

Have you ever reviewed an NDA with similar points? What questions did you ask before signing?

Logging operator for Kubernetes

https://github.com/kube-logging/logging-operator

simple terminal UI for git commands

https://github.com/jesseduffield/lazygit