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Containers · K8s

Docker & Kubernetes

Containerized apps and orchestration when Compose on one box is no longer enough.

  • Containers that run the same locally, in CI, and in prod.
  • Health checks, graceful shutdown, and slim images.
  • Kubernetes when orchestration at scale is real, not aspirational.
  • Helm or plain manifests documented for your ops team.
  • Compose on one VM when that is still the honest answer.
40+ projects since 2022 IST · daily sync NDA-ready
View featured case study
Founder-led team · Surat, India · English-first delivery
WHAT WE OFFER

What we deliver for docker & kubernetes

Core deliverables

  • Slim Docker images
  • Health checks & probes
  • Helm or manifest sets
  • Cluster upgrades plan
  • Cost-aware sizing

Why teams choose this engagement

  • Infrastructure as code and environment parity
  • CI/CD pipelines and automated test gates
  • Monitoring, alerting, and runbooks
  • Security hardening and access reviews
CHALLENGES

Problems we solve in docker & kubernetes

  • Compose on one box cannot scale

    Multi-service products outgrow single-host Docker. We plan K8s migration with health probes and rollback before cutover.

  • Images bloated and slow to deploy

    Fat containers increase cost and startup time. We slim images and cache layers with documented build pipelines.

  • Cluster upgrades feared

    Version drift blocks security patches. We schedule upgrades on staging with workload tests before production.

  • No visibility inside the cluster

    Pods restart silently without metrics and logs correlated to traces. Observability is part of delivery, not optional.

OUR APPROACH

How we build docker & kubernetes

Founder-led engineers in Surat (IST) with morning and end-of-day updates so distributed product owners stay in the loop.

Containers package your app the same way everywhere. Kubernetes when you need orchestration at scale, not for a single small API.

We dockerize legacy apps carefully: health checks, graceful shutdown, and images that are not 2 GB of junk.

Multi-service products that need consistent, repeatable deploys.

CONTAINERS

Docker images production-ready

We containerize Django, FastAPI, and worker services with slim images, health checks, and compose or Helm manifests tested on staging before orchestration.

  • Multi-stage builds and layer caching
  • Liveness and readiness probes defined upfront
  • Local dev parity with staging configuration
KUBERNETES

Orchestration when scale demands it

Kubernetes when replica count and service count justify ops overhead. We deliver manifests or Helm charts with upgrade and rollback plans your team can run.

  • Cost-aware sizing and autoscaling limits
  • Ingress, secrets, and network policies documented
  • Cluster upgrade path tested on non-prod first
INDUSTRIES

Where we apply docker & kubernetes

Vertical experience from shipped products, not generic claims.

WHY US

Why teams choose us for docker & kubernetes

Six reasons founders and product leads pick us over a generalist shop - scoped to how we deliver this engagement.

  • Legacy dockerization

    Monoliths moved carefully without 2 GB junk images.

  • HPA and rolling updates

    When traffic patterns justify cluster ops.

  • Not K8s by default

    Single Django app with low traffic may stay simpler.

  • Retainer ops option

    Cluster care via ongoing support when scoped.

  • Right-sized AWS

    Observability and cost reviews when autoscaling and idle resources grow.

  • Security-minded access

    Least-privilege IAM and reviewed changes, not shared root console logins.

HONEST FIT

Is this for you?

Good fit

  • You run multiple services that need consistent deploys.
  • You are outgrowing manual Docker Compose on one VM.
  • You need HPA and rolling updates.
  • You run multiple services that need consistent deploy artifacts.
  • You are outgrowing manual Docker Compose on one VM.
  • You need rolling updates and health checks in production.

Probably not

  • One Django app, low traffic, no ops team, simpler hosting may suffice.
  • One low-traffic Django app with no ops team - simpler hosting fits.
  • You want Kubernetes before you have observability basics.
  • You need 24/7 cluster management with no retainer budget.
HOW WE WORK

Delivery process for docker & kubernetes

How we package apps in containers and add orchestration only when justified.

We inventory current infra, access patterns, deploy pain points, and console-only changes. Tribal knowledge captured before we propose IaC or pipeline work.

  1. Containerize

    We inventory current infra, access patterns, deploy pain points, and console-only changes. Tribal knowledge captured before we propose IaC or pipeline work.

  2. CI integration

    Terraform or CloudFormation layout, CI/CD stages, and secret management agreed upfront. Plan output reviewed on every infra PR - no surprise production diffs.

  3. Orchestrate if needed

    Dev and staging environments mirror production layout, secrets, and queue topology before live traffic. Smoke tests run on promote, not only on merge.

  4. Document ops

    Metrics, alerts, and runbooks configured and reviewed with your on-call before go-live. Pager routing and Slack hooks tested on staging incidents.

TECHNOLOGIES

Stack for docker & kubernetes

Tools and runtimes we use on this type of engagement - chosen for production delivery, not slide-deck logos.

  • Docker
  • Kubernetes
  • AWS
  • Prometheus
WORKFLOW

How we work on docker & kubernetes

  • GitOps flow

    Infra changes via PR with plan output reviewed.

  • Alert routing

    Pager and Slack hooks agreed before go-live.

  • Runbooks

    Rollback and access docs kept next to the repo.

  • Release coordination

    Deploy windows aligned with your product team.

DEPLOYMENT

Production discipline for docker & kubernetes

  1. Staged promote

    Dev → staging → prod with automated smoke tests at each gate. No direct console edits on production without a tracked change.

  2. K8s health checks

    Readiness probes, liveness probes, and HPA limits configured before traffic. Resource requests sized from staging load, not guesses.

  3. Secrets management

    No plaintext keys in repos, build logs, or Slack. Rotation path documented; staging uses the same secret layout as prod.

  4. Observability

    Metrics, traces, and logs wired before launch - not after the first outage. Alert thresholds reviewed with whoever carries the pager.

OUTCOMES

Track record from docker & kubernetes

Metrics from shipped products and active engagements - not slide-deck claims.

40+
Deploy pipelines built
IaC
Infra in version control
IST
Morning & EOD sync
Runbooks
Before production traffic
CASE STUDIES

Proof from docker & kubernetes

Real products we shipped for founders in the US, UK, and Europe.

Engineering leads ask whether we deploy with rollback docs and staging parity - not one-off console changes before a Friday release.

  • Deploys are still manual

    Production systems below run on CI/CD and documented rollback - not console clicks.

  • Alerts fire with no runbook

    We wire observability and handover docs before traffic hits production.

  • Staging never matched prod

    Featured work shipped through staged promotion with parity checks.

AstroSure.ai - SparkScribe Technologies case study AI & ML · SaaS
Consumer AI 8 months

AstroSure.ai

AI-powered astrology platform with personalized daily guidance

What they needed: The founders had a notebook demo but needed a production LLM pipeline with cost controls, human review, and staging parity before investor diligence.

Our approach: Before build, SparkScribe worked with AstroSure to translate their SaaS Product goals into an actionable plan — not an off-the-shelf template.Discovery & planningWorkshopped birth-chart, daily reading, panchang, kundli matching, and Agastya chat flows against latency …

An astrology platform powered by LLMs - personalized horoscope readings, panchang insights, and conversational guidance through a branded AI assistant.

  • 3× faster reading generation
  • 99.2% API uptime in production
  • Python
  • Django
  • OpenAI
  • PostgreSQL
  • Redis
  • React
  • AWS
View case study
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Hire us

Engagement models for docker & kubernetes

Container and Kubernetes work via fixed-scope dockerization or retainer for cluster operations.

  • Fixed-scope project

    Discovery, written requirements, and milestone billing. Best for MVPs, redesigns, and integrations with a defined end state.

    • Duration: Phased milestones
    • Working: Sprint plan agreed upfront
    • Billing: Per milestone or phase
    • Timeline: Based on signed scope

  • Dedicated squad

    A focused engineering squad on your product: weekly demos, shared backlog, and one accountable team when scope evolves.

    • Duration: 8 hrs/day · 5 days/week
    • Working: ~160 hrs/month capacity
    • Billing: Monthly invoice
    • Timeline: Sprint-based delivery

  • Part-time retainer

    Smaller monthly hour buckets for fixes, dependency updates, and enhancements, with the same engineers when possible.

    • Duration: 4 hrs/day · 5 days/week
    • Working: ~80 hrs/month
    • Billing: Monthly retainer
    • Timeline: Ongoing support window
Mutual NDA before codebase access Morning & EOD IST sync Written scope before sprint one
FAQ

Questions about docker & kubernetes

What prospects ask on a first call about this service: scope, timelines, fit, and how we work.

  • Scope & pricing
  • Delivery process
  • Handover & IP
  • NDA & quality gates
  • Written scope before sprint one milestones, owners, and what stays out of v1 are documented before build starts.
  • Weekly staging demos with the engineers writing your features, not a status deck relay.
  • Your IP in the contract code, designs, and docs transfer to you on agreed milestones.
  • Mutual NDA upfront before you share product details, credentials, or repository access.

5 questions

When do we need Kubernetes versus Docker Compose?

K8s when replicas, autoscaling, or multi-service ops justify complexity. Compose for smaller stable workloads.

Do you write Helm charts or use managed services?

We pick based on your ops team. Managed EKS/GKE/AKS with sane defaults beats bespoke clusters for many teams.

How do you handle secrets in Kubernetes?

External secret stores, no plain manifests in git, rotation steps documented for your security review.

Can you migrate our VMs to containers?

We containerize app tiers first, prove parity on staging, then cut traffic with rollback ready.

What cluster handover do you provide?

Architecture diagram, upgrade playbook, resource requests/limits guide, and on-call cheat sheet.

GET STARTED

Containerizing or moving to K8s? Let's simplify ops.

Describe service count, stateful needs, and team Kubernetes experience. We avoid cluster complexity you cannot operate - Docker Compose is fine when it fits.

  • Images, health checks, and resource limits set.
  • Operate-it-yourself docs included.