Our Redis development services and consulting cover teams that need caching, sessions, rate limiting, pub/sub, and real-time leaderboards — the data layer between your application and your database. Redis or Valkey configured properly, eviction policies matched to your workload, Sentinel or Cluster for HA, and memory management that doesn't surprise you at 3am.
Why Entalogics for Redis
Every Redis deployment we audit has the same problems — no eviction policy so Redis OOMs and crashes, no Sentinel so a single node failure takes the entire cache layer down, keys without TTL accumulating for months, and no monitoring so nobody knows until the application starts timing out.
Default Redis refuses writes once memory fills up, and your application breaks the moment it happens. We configure `allkeys-lru` or `volatile-ttl` based on your actual workload, set TTL on every key that isn't permanent, and leave real headroom on `maxmemory`.
One Redis node is a single point of failure for the entire cache layer. Sentinel handles automatic failover with three or more nodes. Cluster handles horizontal sharding once data outgrows a single node's memory. Tested quarterly, not assumed to work because it was configured once.
Cache-aside for read-heavy data. Write-through when cache and database consistency genuinely matters. Write-behind for write-heavy workloads where eventual consistency is acceptable. Each pattern earns its place by the traffic it actually serves.
`INFO` metrics exported to Prometheus or Datadog. A hit rate under 80% means the cache isn't doing its job. Climbing evictions mean memory is undersized. Climbing connected clients usually means connection pooling is broken somewhere upstream.
When Redis, when Valkey
Redis changed to AGPL in 2024. Valkey forked as the BSD-licensed alternative, and AWS ElastiCache now defaults to it. The technical choice hasn't changed — the licensing and governance question is new, and it genuinely matters. We'll tell you on the first call which fits.
USE REDIS WHEN
USE VALKEY WHEN
WE SAY NO WHEN
What we build on Redis
Eight ways this work shows up for real clients. Each one configured for production, not left on defaults.
Cache-aside with proper TTL, eviction, and invalidation. The layer between your app and your database that cuts query load by 80-95%.
Centralized sessions across application instances. Rate limiting per user, per IP, per API key. Sliding windows and token buckets implemented in Redis, not scattered across your app.
Redis Pub/Sub for real-time notifications. Redis Streams for persistent messaging with consumer groups. The messaging layer that doesn't need Kafka.
Sentinel for automatic failover. Cluster for horizontal sharding. Configured, tested, and monitored, not just deployed and left alone.
Drop-in migration for standard workloads. Module dependency audit for RediSearch and RedisJSON users. Zero-downtime cutover through replica promotion.
Redis Vector Sets for embedding storage and similarity search alongside your existing cache and session data, without standing up a separate vector database.
Memory analysis, key distribution audit, pipeline batching, Lua script optimization. The Redis that handles 500K ops/sec, not the one that OOMs at 50K.
Ongoing monitoring, eviction policy reviews, and failover testing — so the cache layer we stabilized doesn't quietly drift back into the OOM crashes and blind spots we were hired to fix.
The playbook
Patterns from real production deployments, not `SET`/`GET` tutorials.
P01
No key without an expiration unless it's genuinely permanent. `SETEX` and `EXPIRE` on every write. No memory leak from forgotten keys accumulating for months.
P02
`allkeys-lru` for general caching. `volatile-ttl` for mixed permanent and temporary keys. `noeviction` only when memory is sized to fit the entire dataset with room to spare.
P03
Multiple commands batched into a single round trip. A hundred individual `GET` calls become one pipeline. Latency drops from 100ms to 2ms.
P04
Quorum-based failover. Sentinel monitoring every replica. Failover tested quarterly with measured recovery time, not assumed to work.
P05
`service:entity:id:field` naming. Consistent namespaces. Scannable patterns. No flat keys colliding across services.
P06
Memory usage, hit rate, evictions, connected clients, replication lag — all exported and alerted. Cache health visible before the application notices a problem.
Signature case
A B2B SaaS platform using Redis as the API cache — `noeviction` policy causing OOM crashes twice a month, no Sentinel so each crash meant 5 minutes of downtime, 40% of keys without TTL accumulating for 8 months, and no monitoring beyond application timeouts. Configured `allkeys-lru`, deployed Sentinel with 3 nodes, added TTL to all keys, and wired Prometheus monitoring in 5 weeks. Zero OOM crashes since. Cache uptime at 99.99%.
Before
noeviction · OOM crash 2x/month · single node · 40% keys no TTL · no monitoring
After
allkeys-lru · 0 OOM crashes · Sentinel 3-node · TTL on all keys · Prometheus dashboard
Industries we serve
We've delivered Redis and Valkey development services for SaaS platforms, eCommerce, gaming, and fintech — anywhere sub-millisecond latency and cache reliability directly affect the user experience.
Engagement shape
Node by node. The current cache stays live the entire time we work.
Two senior Redis engineers. Memory analysis, key TTL audit, eviction policy review, HA configuration check. A ranked, dollarized plan.
Eviction policy configured, TTL enforced, Sentinel or Cluster deployed. Measurable stability improvement visible in week two.
Pipeline batching, Lua scripts, monitoring configured, Valkey migration if applicable. Your application keeps running throughout.
Prometheus dashboard live, Sentinel tested. Runbook handed to your team — or we stay on for Redis support and maintenance.
Stack
Our default Redis development stack — picked for production.
Verified feedback from Upwork, Clutch, and reference calls we're happy to set up before you sign anything.
CEO, Modestly
Entalogics has successfully delivered extension prototypes on time, and we are impressed with their project management and the finished product. The client communicates with Entalogics via virtual meetings, email, and messaging apps.
Founder, Flourish Schools
Collaborating with Entalogics was a great experience. Communication was clear, we aligned quickly, and their team delivered high-quality code on time with thoughtful technical decisions.
CTO, SentryBay
Their Chromium expertise helped us ship a hardened browser with live threat controls and enterprise rollout support. Security operations became significantly faster.
Founder, G3 Ventures LLC
Entalogics delivered our custom Electron browser in six months with isolated profile workflows and stable policy sync. Agent onboarding improved by 55% after rollout.
Project Manager, Sociall
Entalogics built our iOS Chromium-based mobile app with a smooth native feel, stable media rendering, and reliable sync. We shipped faster and improved engagement after launch.
RozmeriGPT
The web dashboard and Chrome extension now share prompts, billing, and analytics in one platform. Our content turnaround improved 4x after launch.
Project Manager, Omni Browser
Entalogics built our Omni Browser on top of Chromium with deep product-level execution. They implemented an integrated VPN and Omni Crypto Wallet directly in the browser, made strong architectural decisions, and delivered quality code on schedule with clear communication.
Project Manager, Digital Office: Aura
Entalogics built Digital Office: Aura as a custom Chromium-based authentication platform. Their team modified Chromium internals and integrated our manual custom authentication flow with reliable implementation, fast delivery, and consistent communication.
Engagement
No hourly billing for thinking time. Fixed quote or a transparent monthly rate.
Fixed scope, fixed price, senior-only team. Architecture to production in 4-8 weeks.
FIXED SCOPE
Senior backend engineers specializing in caching architecture, embedded in your team. Pause, resize, or exit with 30 days' notice.
PER ENGINEER
A standing partner for data-layer performance — cache architecture, Valkey migration, Pub/Sub scaling, hiring help.
PROCUREMENT-FRIENDLY
Senior engineers
Thirty minutes with a senior Redis engineer, the relevant playbook, and a candid read on whether Redis, Valkey, or a different caching architecture fits your data layer best.
