Cut Costs and Boost Control by Replacing Azure Redis with Open-Source Memcached

It began with an uncomfortable realization during a routine cost review: our multi-region Azure deployment—intended to elegantly scale and secure a set of modest cloud services—was bleeding more than $5,000 each month on a basic caching strategy. The core culprit was Azure Cache for Redis (Premium), whose advanced isolation and network features had compelled us away from the intended simplicity—and price point—of Redis’ standard tier. Despite our workloads being light, the requirements were not: every region and environment in our estate needed its own private, VNet-integrated cache for compliance, forcing us into a premium pricing trap we never meant to navigate. This is the in-depth story of how we reconsidered our requirements, challenged our assumptions, and ultimately swapped out Azure Redis for open-source Memcached—saving thousands without giving up operational safety or scalability.

Azure Cache for Redis: The High-Cost of Compliance​

Cloud architects often warn that in the world of on-demand services, surprises lurk in the details. We believed our caching workload was benign: less than 200 MB of frequently rewritten keys, refreshed on roughly an hourly basis—a textbook definition of a “simple cache.” At first, Azure Cache for Redis Standard had served us well. Its speed, high-availability, and managed nature meshed well with our platform-as-a-service (PaaS) approach.
But our software stack soon faced a critical compliance update. Security and infrastructure teams decreed every service—databases, message brokers, and yes, even transient cache layers—must be isolated within Virtual Networks (VNets). This ensured that network traffic never traversed the public internet, protecting data-in-transit and tightly controlling network access. Unfortunately, at the time of our migration, Azure Cache for Redis only enabled VNet integration at the Premium pricing tier—a tier engineered for far heavier, larger-scale, and more mission-critical workloads.
This “one-size-fits-all” approach to security wasn’t just an annoyance. The price gap was palpable: Redis Premium started at hundreds of dollars per instance, and our multi-environment, multi-region setup required several distinct caches. For functionality we barely needed—true high-availability, clustering, active-active geo-replication—we were paying as if we’d built a real-time analytics engine. Trying to optimize instance count or resize downward made little impact thanks to non-negotiable baseline pricing.
Our cache was theoretically “enterprise ready,” but the bill was hard to justify to investors, especially since we were storing nothing a plain-old memcache couldn’t handle.

Redis vs. Memcached: Which Caching Tool Makes Sense?​

For the uninitiated, Redis and Memcached share a core mission: they’re both in-memory key-value stores that offload reads and writes from traditionally slower storage layers. Yet under the hood, key differences dictate their real-world value:

• Redis is a multi-faceted data store, supporting complex structures (hashes, lists, sets, sorted sets) alongside simple key-value pairs. It boasts persistence options, built-in replication, scripting, clustering, and fault tolerance features—making it popular for both cache and full secondary data store use cases.
• Memcached, by contrast, is ruthlessly simple. It is a pure slab-allocated, memory-only key-value cache, designed for speed, horizontal scaling, and ephemeral workloads. It has no persistence, replication, or native clustering—but achieves impressive throughput for straightforward caching scenarios.

We took a critical, data-driven look at our requirements:
Our actual needs—stateless, ephemeral, basic key-value caching—could easily be addressed by Memcached. The only missing features, like out-of-box clustering or persistence, were unnecessary for our use case. What we needed was basic, fast, isolated RAM cache inside a secure network—without the “tax” of a managed Redis Premium instance.

Building a Production-Grade Memcached Deployment on Azure​

With our requirements clarified, the next challenge was operational: how do you reliably run Memcached in Azure, given there’s no official managed PaaS for it? Our criteria were simple: secure VNet integration, low maintenance, good visibility, and—ideally—“set and forget” reliability.

Deployment Options Considered​

• Azure VMs (Virtual Machines): The classic—but now old-school—way to run open-source daemons in the cloud. Spin up a lightweight Linux VM per region, install Memcached, and expose it to internal services over a dedicated subnet.
• Containerized Memcached (AKS/ACI): Modern best practice would argue for running Memcached as a containerized deployment, either on Azure Kubernetes Service (AKS) or as an Azure Container Instance (ACI) for simple, single-container workloads.
• Third-Party Managed Services: Some Azure marketplace vendors offer managed Memcached clusters, but these often bundle markup and deploy under the hood to VMs or containers.

We chose containerized Memcached running on AKS due to:

• Integrated security: Isolated using Kubernetes network policies and internal-only service endpoints
• Elastic deployment: Easily scale pods per environment needs without downtime
• Automation: Use Helm charts and Azure DevOps pipelines for fully automated rollout and recovery
• Unified monitoring: Use built-in Azure Monitor and Prometheus exporters to track cache stats, errors, and resource usage

Security and Compliance​

Unlike Redis Standard on Azure, where you’re locked out of VNet integration, self-hosted Memcached lets you fit the service inside your exact network topology. We used network security groups and private IPs to restrict cache access only to known web and API services. All management was restricted via AKS RBAC; node pools had no public IP or SSH enabled.
To verify compliance, every deployment was scanned using our cloud security suite for open ports, non-compliant firewall rules, and unwanted internet exposure. Secrets were stored in Azure Key Vault, injected at pod runtime, never hard-coded or checked into source.

Sizing and Reliability​

For our load—less than 200 MB of cache, peaking at around 5,000 requests per second—the smallest available VM size or Kubernetes node was more than sufficient. We configured liveness and readiness probes so that if Memcached pods were ever unresponsive, Kubernetes would roll out a fresh container within seconds, with no service disruption. Backups were unnecessary given the cache’s ephemeral design.

Operational Overhead​

One tradeoff: running Memcached on AKS or VMs moves patching, upgrades, and scaling back into your hands. This is the price of flexibility, and while it adds some ops burden, modern tooling like automated container upgrades, blue-green deployment pipelines, and health checks minimized this to a few minutes of hands-on work each month.

Real-World Impact: Savings, Stability, and Lessons Learned​

After moving all environments and regions to our self-hosted Memcached implementation, our Azure Redis Premium bill evaporated. Costs dropped from over $5,000/month to under $400, covering the managed Kubernetes service, underlying VM scale sets, and minimal operations overhead. We reserved significant cloud budget for other, business-critical initiatives.

Performance Observations​

• Latency: End-to-end cache GET/SET roundtrips fell by several milliseconds versus managed Redis, likely due to closer co-location to app servers and less overall abstraction.
• Stability: Uptime for Memcached on AKS has been effectively 100% since deployment, with automated failover in place.
• Scaling: AKS horizontal pod autoscaling lets us seamlessly absorb traffic spikes in any region without provisioning costly always-on replicas.

Productivity and Flexibility​

Our team is now free from the paradox of managed service rigidity: open-source Memcached lets us tweak instance limits, patch on our own schedule, and move cache endpoints around without updating cloud contracts or navigating multi-week vendor escalations.

Critical Analysis: Strengths and Strategic Trade-offs​

Notable Strengths​

• Cost Efficiency: The most obvious benefit; Memcached is free and highly resource-efficient. We were able to right-size compute without being locked into Azure’s Redis Premium SKU structure.
• Network Security: Hosting our own cache meant we could implement VNet isolation and firewall rules without being boxed into Microsoft’s tier-based feature gating.
• Transparent Operations: With open-source software and Kubernetes-native tooling, we gained full insight and control over runtime, logs, and upgrades.
• Simplicity: Memcached’s design is perfect for plain key-value use cases. Application integration is trivial, with widespread language support and robust client libraries.

Potential Risks and Cautionary Notes​

• Operational Responsibility: You’re trading managed peace of mind for control. All software patching, DDoS protection, scaling, and incident response now fall to your team. For teams lacking DevOps maturity, this can backfire.
• No Persistence or Replication: Memcached is stateless by design. Any node restart or rolling upgrade wipes the cache. For scenarios needing high availability or data retention, Redis may still be justified.
• Manual Scaling: While Kubernetes’ HPA helps, there is no “click to scale” as you’d get in a true PaaS. Edge cases (node/pod failures, Azure outages) require careful monitoring and failover planning.
• Limited Feature Set: If your organization grows into using Redis’ more advanced features (streams, geospatial queries), migrating back becomes costly and involved.
• Lack of Azure Support: With Redis Premium, you buy into Azure’s full SLA and support coverage. DIY open source means you rely on community forums and general cloud support only.

Is Managed Redis in Azure Ever Worth It?​

Deciding whether to stick with managed Redis or roll your own Memcached boils down to risk profile, compliance, engineering bandwidth, and functional needs.
Consider Azure Cache for Redis Premium if:

• You need enterprise SLAs for large teams or mission-critical, multi-user apps.
• Your cache layer must handle advanced data types, multi-region replication, or be persistent.
• Your DevOps team is small, less cloud-native, or needs Azure's 24/7 support.

Choose Memcached if:

• Your caching needs are simple, ephemeral, and stateless.
• Cost sensitivity is high and you’re comfortable running VMs or Kubernetes workloads.
• Security and compliance are met via private networking and app-layer protections.
• You value customization and minimal vendor lock-in.

Broader Implications for Cloud-Native Application Design​

This case highlights a key theme of modern cloud architecture: managed services, while convenient and powerful, often enforce a lowest-common-denominator approach. Features are “gated” behind tiers that may not suit your true needs, with pricing models crafted for Azure’s scale, not yours.
Open source remains a powerful counterbalance—especially as containerization and infrastructure automation tools remove much of the historical pain of self-hosting. The rise of loosely coupled, cloud-native stacks means organizations can increasingly mix and match open-core and managed services on their own terms.
Yet the operational responsibilities for critical systems in production cannot be understated. For organizations on a growth arc, maintaining clear documentation, disaster recovery runbooks, security hardening, and observability will all be equally critical as cost savings.

Conclusion: Maximizing Value without Sacrificing Security​

The journey from Azure Redis Premium to Memcached was not just a cost optimization—it was a reckoning with what “managed” actually means, and a reminder to continually evaluate every baseline as your usage patterns or compliance postures shift.
For us, the calculated gamble paid off, delivering equivalent cache reliability and performance at a fraction of the cost. But success required the right mix of cloud ops maturity, upfront investment in automation, and an honest assessment of risk tolerance.
For Windows and .NET teams architecting secure, scalable cloud apps, the story here is clear: don’t let the tool dictate your architecture. Trust your requirements, know the market landscape, and be willing to re-examine decisions as your business, cloud, or compliance requirements evolve. Sometimes, “back to basics” with open-source software is the boldest modernization you can make—even in the heart of enterprise Azure.

---

---

Source: InfoWorld How we replaced Azure Redis with Memcached