Welcome! Simplifi'ED is now Omnivya. We're excited to announce that Simplifi'ED has evolved into Omnivya! This transformation reflects our commitment to serving you even better, with expanded expertise in Cloud Native, Kubernetes, GreenOps, FinOps, and DevSecOps. Our new brand embodies innovation, sustainability, and security so you can accelerate your digital journey with confidence. Thank you for trusting us as your technology partner! Learn more

Area of expertise

Distributed systems

A distributed system can look stable while networks, dependencies, and data behave as expected. Defects emerge when ordering, time, or availability can no longer be treated as reliable assumptions.

Operational definition

Distributed systems expertise analyses consistency, concurrency, communication, storage, failure modes, and recovery to make actual guarantees explicit.

Problems actually encountered

  • 01

    Duplicates or loss during recovery

  • 02

    Timeouts and retries amplifying saturation

  • 03

    Implicit consistency differing across components

  • 04

    Synchronous dependency turning local failure into global failure

Decisions involved

  • Choose consistency and idempotency guarantees
  • Define timeout, retry, and backpressure budgets
  • Balance partitioning, replication, and recovery

Common errors

  • Treating the network as reliable
  • Adding retries without a global budget
  • Confusing claimed exactly-once delivery with exactly-once business effects

Signals that external expertise becomes useful

  • An incident cannot be reproduced in isolation
  • Load triggers non-linear behaviour
  • A migration changes data or delivery guarantees

Omnivya method

  1. 1.

    State expected invariants and guarantees

  2. 2.

    Map protocols, state, and dependencies

  3. 3.

    Replay timelines and failure scenarios

  4. 4.

    Compare corrections by safety, cost, and complexity

Possible deliverables

  • State, flow, and invariant model
  • Causal analysis of distributed behaviour
  • Correction options with validation scenarios

Evidence of reasoning

  • Invariants expressed in testable form
  • Incident timeline connected to mechanisms
  • Repeatable failure and recovery tests

Browse public work

Explicit limits

  • No promise to eliminate every failure
  • No microservices proposed as a default
  • No hiding an impossible guarantee behind a product

Related mission formats

Frequently asked questions

Can you investigate a non-reproduced incident?
Yes, when logs, traces, state, or timelines allow hypotheses to be tested without claiming unavailable certainty.
Must the architecture be replaced?
Rarely as a first response. A clarified guarantee, corrected protocol, or bounded dependency may be sufficient.
Can you validate a data migration?
We can review guarantees, cutover, reconciliation, and rollback scenarios; execution remains with accountable teams.

Analyse distributed-system behaviour

If this tension is yours, let’s frame the decision before widening the scope.

Analyse distributed-system behaviour