TechOps Examples
Hey — It's Govardhana MK 👋
Welcome to another technical edition.
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Last year, a DevOps team told us: “Our traffic didn’t grow. Our users didn’t grow. So why did our cloud bill grow 28%?”
The answer? Rollouts.
They were using Argo Rollouts (smart move).
But every new version meant: Extra pods, Temporary over-provisioning, Resources that never scaled back correctly
They were paying for “safety” …twice.
That’s why on March 3 at 12:00pm ET, we’re running
We’ll show you:
A simple 6-step framework to reduce Kubernetes waste
How to optimize during Argo Rollouts
How teams cut costs without risking reliability
If you run Kubernetes in production, this is not optional.
IN TODAY'S EDITION
🧠 Use Case
When Microservices Architecture Becomes Overengineered
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🧠 USE CASE
When Microservices Architecture Becomes Overengineered
One cannot take away these debates from a DevOps and Cloud engineer's lives:
Monolithic vs Microservices
Serverless vs Self-Managed Virtual Instances
Kubernetes vs Do we really need Kubernetes?
As a matter of context, let’s pick “microservices” for today. If I have to explain the difference in one line:
Monolithic architecture is a single, tightly integrated application where all components function as one unit.
Microservices architecture is a design where the application is split into independent services communicating via APIs.
Microservices can revolutionize how you build and scale systems - but only when used in the right context.
Misaligned complexity can create a real problem, not the architecture itself.
Imagine a spectrum.
On the far left, your system has a manageable number of services:
🟨 ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️
On the far right, the system has fragmented into too many services:
⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ 🟦
The red square on the left is where microservices worked well initially:
🟨 ⬜️ ⬜️ 🟥 ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ 🟦
The green square is where the system ended up, due to uncontrolled growth:
🟨 ⬜️ ⬜️ 🟥 ⬜️ ⬜️ ⬜️ ⬜️ ⬜️ 🟩 ⬜️ ⬜️ 🟦
The gap between 🟥 and 🟩 is the misaligned complexity.
You can call it “the microservices sprawl”
Red Flags to Identify When Your Microservices Architecture is Becoming a Bad Idea:
🚩 Duplicate functionalities across multiple services.
🚩 Wasted resources on scaling less critical services.
🚩 Poor visibility into service health and dependencies.
🚩 Frequent cascading failures due to interdependencies.
🚩 Overlapping responsibilities with unclear service ownership.
🚩 Complex inter-service communication slows down troubleshooting.
In short, It’s the result of too many services, fragmented ownership, and poor boundaries. Unless you bring this under control, microservices will become a liability.
There are two ways to fix the sprawl:
1. Streamline and consolidate services
Merge services with overlapping functionalities
Reduce the granularity of services where it’s unnecessary
Centralize non-critical shared services
2. Improve operational management
Introduce robust service discovery and dependency mapping tools
Enforce architectural boundaries and team ownership
Use automation for scaling, monitoring, and troubleshooting
We’re bringing a hands-on Kubernetes Optimization workshop to show you how to stop the waste without breaking your deployments.
You’ll learn:
• A simple 6-step framework to cut Kubernetes costs
• How to optimize workloads even during Argo Rollouts
• Real examples from teams who reduced cost and improved reliability
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