ContentPosts from @moha..
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@faun shared a link, 1 week, 3 days ago

How AWS S3 serves 1 petabyte per second on top of slow HDDs

AWS S3 doesn’t need fancy hardware. It wrings performance out ofcheap HDDs,log-structured merge trees, anderasure coding. The trick? Shard everything. Hit it in parallel. Randomized placementdodges hotspots.Hedged requestsrace the slowest links. And when things get lopsided, S3 rebalances - constant..

How AWS S3 serves 1 petabyte per second on top of slow HDDs
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@faun shared a link, 1 week, 3 days ago

Seven Years of Firecracker

AWS is puttingFirecracker microVMsto work in two fresh stacks:AgentCore, the new base layer for AI agents, andAurora DSQL, a serverless, PostgreSQL-compatible database it just rolled out. AgentCore gives each agent session its own microVM. More isolation, less cross-talk - solid for multistep LLM wo..

Seven Years of Firecracker
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@faun shared a link, 1 week, 3 days ago

Automated GitHub Self-Hosted Runner Cleanup: Lambda Functions and Auto Scaling Lifecycle Hooks

When an EC2 instance in an Auto Scaling Group shuts down, event-driven plumbing kicks in. Alifecycle hookcatches the scale-in, fires off an SNS notification, and triggers aLambda. That Lambda calls the GitHub API to yank the self-hosted runner before the instance dies. No dangling runners. No manual..

Automated GitHub Self-Hosted Runner Cleanup: Lambda Functions and Auto Scaling Lifecycle Hooks
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@faun shared a link, 1 week, 3 days ago

How LogSeam Searches 500 Million Logs per second

LogSeam rips through500M log searches/secand pushes1.5+ TB/s throughputusing Tigris’ geo-distributed object storage. It slashes log volume by 100× with Parquet + Zstandard compression. Then it spins up compute on the fly, right where the data lives—no long-running infrastructure, no laggy reads...

How LogSeam Searches 500 Million Logs per second
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@faun shared a link, 1 week, 3 days ago

Internal HTTPS Routing in Istio.

Istio finally bringsinternal HTTPS routingwithSNI-based traffic rules. Services in the mesh can now talk over port 443—TLS fully intact. Just like in prod. TLS terminates at the ingress gateway. Routing pivots on SNI, not headers. Which makes this much closer to real-world mTLS flows. What’s the pla..

Internal HTTPS Routing in Istio.
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@faun shared a link, 1 week, 3 days ago

How I Built My Kubernetes Command Toolkit: A Journey from kubectl Chaos to Command Mastery

A dev-built Kubernetes CLI framework reshapeskubectlfor how teams actually work. Commands get grouped by role - dev, SRE, sec, admin - instead of by resource. It bakes in defaults forKyvernopolicies, encourages muscle-memory workflows, and wires up real-time troubleshooting to shrink downtime in pro..

How I Built My Kubernetes Command Toolkit: A Journey from kubectl Chaos to Command Mastery
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@faun shared a link, 1 week, 3 days ago

Introducing Headlamp Plugin for Karpenter

The newHeadlamp Karpenter Pluginwires real-time autoscaling insight straight into the Headlamp UI. It showsKarpenterresources, live metrics, scaling moves—no kubectl spelunking required. NodePoolsandNodeClaimsget mapped to core Kubernetes objects. You can tweak configs in the UI, get validation on t..

Introducing Headlamp Plugin for Karpenter
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@faun shared a link, 1 week, 3 days ago

Most Cloud-Native Roles are Software Engineers

Software Engineers still own the cloud-native job boards in 2025 - nearly47%of all Kubernetes-tagged listings. DevOps holds onto second. But Platform Engineers just leapfrogged SREs, which have slid 30% since 2023...

Most Cloud-Native Roles are Software Engineers
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@faun shared a link, 1 week, 3 days ago

The Myths (and Costs) of Running Node.js on Kubernetes

Kubernetes struggles to scale Node.js efficiently due to a mismatch in resource usage patterns. Autoscaling can be sluggish with bursty traffic, leading to revenue risks and performance issues. Teams must rethink resource allocation and scaling strategies to optimize Node.js efficiency in Kubernetes..

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@faun shared a link, 1 week, 3 days ago

Kubernetes for agentic apps: A platform engineering perspective

Agentic AI flips the old model. Instead of stateless, event-by-event workloads, we getstateful, self-steering systemsthat observe, reason, plan, and act - on loop. Kubernetes steps up as the OS for this next phase. Boosted by platform engineering, it brings the right mix:ephemeral compute, persisten..

Kubernetes for agentic apps: A platform engineering perspective