Shameem Abdul Salam

Platform and DevOps engineer with extensive experience designing, operating, and scaling AWS-based systems. Recent focus: scientific batch workloads on AWS Batch, multi-region Terraform, hybrid integrations for laboratory data platforms, and regulated-environment operations (KMS, IAM, observability). Strong background in CI/CD, Docker, ECS, GitLab/GitHub pipelines, e-commerce infrastructure, cloud cost optimization, and technical leadership.

Lab-to-AI: From Raw Zone to SageMaker and HealthOmics

The science team’s request arrived as four words: “AI on our data.” Behind it stood a platform team with a validated raw zone, a governance model built for audits, and no plan for what happens when a model wants to read everything.

Observability as Audit Evidence

Mid-investigation, someone asked for the transfer logs from eleven weeks ago—the ones that would show exactly what happened to run R. The retention policy was thirty days. The logs that could have answered the question had been rotated into nothing, and the finding closed as “probable, not demonstrable.”

Validated Delivery: CI/CD Under GxP Change Control

The validation auditor asked for the change record behind a production change made two weeks earlier. The honest answer was a Slack thread, a terraform apply from someone’s laptop, and a Jira ticket with no attachments. None of that is a change record.

Should Your Raw Instrument Zone Become Iceberg?

The science team asked a reasonable question: “Can we query two years of run metadata without a week of Athena scans?” The raw prefix held forty million objects, LIST calls were timing out, and every dashboard paged through keys like it was 2013.

Instrument Ingestion Patterns: Poller, DataSync, or S3 Events

Three instruments, three capabilities. One writes finished runs to a Windows share. One can call the S3 API directly. One ships files over SFTP to wherever you point it. The team forced all three through one custom poller—and spent a year paying for it in special cases.

The ALCOA+ Field Guide for Platform Engineers

The auditor asked a simple question: “How do you know this file was not modified after upload?” The team had versioning off, a shared transfer credential, and a fourteen-second silence that felt much longer.

Amazon Linux 2 Is EOL: a Migration Checklist for Batch, ECS, and Lambda

The security scan flagged eleven CVEs on the ECS instances. There was nothing to patch with—Amazon Linux 2 went end-of-life on June 30, 2026, and the fixes simply stopped coming. The AMI had been “temporary” for two years.

Hybrid Lab-to-Cloud: a Go-Live and Recovery Checklist

The pilot worked for one instrument on a quiet Tuesday. Cutover week added three instruments, a VPN blip, and a KMS key rotation—and the only recovery plan was “call the person who built the agent.”

Observing and Debugging Hybrid Data Transfers

Slack said “files aren’t in S3.” The agent host said “fine.” CloudWatch had three log groups and no shared id. Twenty minutes later someone found the run under a different instrument prefix—and a completion marker that never wrote.

Idempotent Pollers, Retries, and Quarantine Paths

The agent crashed after uploading 40 of 42 files. On restart it uploaded everything again, overwrote nothing useful, emitted two completion markers, and the pipeline ran twice—once on a partial set that somehow got marked ready during the race.

IAM and KMS Across the Hybrid Lab–Cloud Boundary

Transfer logs said AccessDenied. The bucket policy “allowed S3.” Someone added s3:* on the role and it still failed—because the objects used SSE-KMS and the key policy never trusted the transfer identity.

Moving Instrument Data to S3 Reliably

The object existed in S3. Size looked right. Downstream parsing failed because the transfer cut off mid-write and a later retry never ran—or ran into a different key. Metrics said “uploaded.” Science said “garbage.”

Hybrid Lab-to-Cloud: Map the Data Path Before Building It

The transfer agent was “done.” S3 had objects. Downstream Batch jobs still saw empty prefixes for hours. Nobody could say whether the instrument was late, the poller was stuck, or a completion marker never arrived.

AWS Batch on EC2: a Deployment Checklist

This post is for teams running compute-heavy workloads on AWS Batch with EC2—genomics pipelines, media processing, ETL, simulations—not for “hello world” Fargate tutorials. It assumes you already have a container image, a VPC, and a reason to use Batch instead of ECS or Lambda.

From Varnish and Drupal Tuning to Platform Engineering

In 2013 I wrote about Varnish in front of Drupal and where Drupal sites actually lose performance. The stack was Apache, PHP, MySQL, SSH, and a lot of hand-tuning. Today I work on AWS Batch, multi-region Terraform, and hybrid lab-to-cloud integrations in life sciences. The logos changed; the job did not.

CloudWatch Logs Insights: 8 Queries I Reuse in Production

This post is for teams already shipping workloads to AWS who reach for the CloudWatch console when something breaks—but re-type the same Logs Insights query from memory every time. It is not a replacement for APM or full distributed tracing, and it assumes your apps write structured or semi-structured logs to CloudWatch.

Terraform Module Layout I Use for Multi-Environment AWS

This post is for teams already running Terraform in AWS who have felt the pain of three “similar but not quite the same” environment folders. It is not a Terraform 101 tutorial, and it assumes you know what a module, variable, and remote state backend are.

GitHub Actions to ECR to ECS: a Deployment Checklist

This post is for teams already running workloads on Amazon ECS who want a reliable GitHub Actions pipeline without reinventing the wheel each release. It is not a greenfield Kubernetes guide, and it assumes you have a working cluster, service, and task definition—not a blank AWS account.

The Blog Is Back on shameem.in

I used to write about Linux, Drupal, caching, and open-source tooling on LinfoPage.Com and my Blogger site. Those posts are from a different chapter — support engineering, LAMP stacks, Varnish, and early Raspberry Pi days — but they are still useful reference material.

Bug in Bash Shell Creates Big Security Hole on UNIX/Linux

A security vulnerability in the GNU Bourne Again Shell (Bash) — the command-line shell used in many Linux and Unix operating systems — could leave systems open to exploitation by specially crafted attacks.

How to Improve the Performance of Drupal Sites

A site is only as fast as its last mile connectivity. If users access a site from a slow connection, even a site capable of responding quickly to requests will appear to be slow. A content management system like Drupal throws in additional challenges to the Web architect in improving performance because, typically, the Apache process takes up more space than a site serving traditional HTML or PHP pages. Read on to take a look at the various external factors that impact performance, and explore ways to mitigate them.

Cache HTTP Reverse Proxy Using Varnish on Ubuntu with Drupal 7

Varnish Cache is a web application accelerator also known as a caching HTTP reverse proxy. You install it in front of any server that speaks HTTP and configure it to cache the contents. Varnish Cache is really, really fast. It typically speeds up delivery with a factor of 300 – 1000x, depending on your architecture.

Busting The Biggest Myths About Linux

For many years Windows was the only operating system for many computer users. In fact, a majority of these users even didn’t know that there was any other OS in the world. And for this reason, Linux, the free and open-source operating system was totally alienated. And slowly when people started to hear about the Linux based OS, many misconceptions started to cloud the free flow of the free and open source OS. So here we are trying to put some light on the real facts by killing the popular misconceptions!

How Linux is Built

Hi Guys, I am back to blogging after a short time. I happy to inform you all that I have got a Job in a company as Open-Source Support Engineer by fulfilling my ambition of placing my career in Open-Source.