Microservices
We track 17 posts about Microservices from 10 engineering blogs. Most active: Nicolas Fränkel, JobTeaser, Soundcloud. Latest post: Oct 4, 2026.
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Security Baked Into the JVM: no single party controls the outcome (opens on the source site)
A URL is a name, and names get reused. Replace the bytes behind https://repo.example.org/order-processor.jar and every permission granted to that URL still applies, now to code nobody audited. So far in this series, Part 1 declared constraints on a remote call, Part 2 vetted code before a client loaded it, Part 3 established who is calling, and Part 4 carried that chain of identities across the wire.
Building ASGI Microservices with Cloudflare Python Workers in Production (opens on the source site)
Deploy a Python ASGI microservice on Cloudflare Workers: Pyodide cold-start mitigation, async subrequest handling, and KV-backed state caching. Continue reading Building ASGI Microservices with Cloudflare Python Workers in Production on SitePoint.
Microservices vs Monolithic Architecture: What Nobody Tells You Until You've Lived Through Both (opens on the source site)
null Continue reading Microservices vs Monolithic Architecture: What Nobody Tells You Until You've Lived Through Both on SitePoint.
Security Baked Into the JVM: sixteen Subjects on the wire (opens on the source site)
Alice calls the order service. The order service calls the ledger on her behalf. At the second hop, the ledger has to decide whose authority the debit is being made under. Most stacks answer badly. Forward Alice’s bearer token verbatim, and the ledger cannot tell her from the service that relayed it. Drop the token and the ledger sees a machine, with no record that a human started the chain. Neither option lets the ledger authorize the combination.
Modular Monoliths: Creating Real Boundaries Before Reaching for Microservices (opens on the source site)
A deep dive into modular monoliths, from module APIs and database ownership to cross-module communication, architecture tests, incremental migration, and the signals that justify microservices. Read more
Security Baked Into the JVM: two Subjects, one call (opens on the source site)
The constraint system stops a bad call before it leaves the JVM. The Safe Codebase Audit Pipeline stops bad code before a client ever loads it. What remains is identity: who is calling, and can you verify it? Most frameworks answer with a token check at the door. A filter validates a bearer token, sets a thread-local variable, and hopes that nothing downstream forgets to look at it. DirtyChai answers differently.
Security Baked Into the JVM: the Safe Codebase Audit Pipeline (opens on the source site)
In Part 1, the minimal deployment showed constraints traveling with the proxy: authentication, encryption, hardened deserialization, all declared in configuration and enforced at the call boundary. The proxy is a JAR. That JAR was downloaded and unmarshalled before any constraint ran. That step is the earlier problem. Distributed Java systems that load remote code are vulnerable to supply chain compromise: an attacker can replace a legitimate JAR with one containing malicious bytecode.
Security Baked Into the JVM: why fork Apache River and OpenJDK? (opens on the source site)
The more distributed a system, the harder it is to secure. Code crosses JVM boundaries. Objects are serialized across trust boundaries. Third-party proxies run inside your process. The usual answer is a network firewall. It helps, but it operates at the wrong level. Java 17 deprecated the SecurityManager, Java 24 put the final nail in its coffin. Most developers didn’t notice.
Authentication between microservices using Kubernetes identities (opens on the source site)
Learnk8s ·
Learn how you can secure communications between microservices to prevent unauthenticated requests using Kubernetes identities.
Efficient Distributed Unique Timestamp Identifier Generation (opens on the source site)
Distributed unique timestamp identifiers provide a powerful means of generating globally unique, human-readable 64-bit values at sub-microsecond speeds. By embedding a host identifier directly into a nanosecond-resolution timestamp, you gain a simple, chronologically sortable, and intuitive scheme for correlating events across multiple hosts. This approach offers significant benefits in latency-sensitive systems where even small delays can become expensive at scale. Introduction In a world of horizontally scaled microservices, ensuring that each event or message receives a unique identifier…
Data replication across backend services with Kafka and Protobuf (opens on the source site)
The Jobteaser application contains a lot of different relatively independent modules to help universities provide career guidance to students: a job board, a career event management system, a career advice appointment management system…When we decided to migrate our application’s backend from a monolith to a service-oriented architecture, we strived to keep each module as isolated as possible from the others in the event of an incident. If the career appointment system was down, students should still be able to browse and apply to job ads.That isolation is achieved through what we’ve called…
Layers vs Silos, a tale of 2 microservice architectures (opens on the source site)
When it comes to the communication between microservices, there are 2 possible extremes:All-sync: whenever a service needs data from another service, it fetches it via a synchronous API call (REST, gRPC, GraphQL). Service calls service calls service… which tends to evolve into layers of APIs, where each layer has dependencies on the next.All-async: no sync calls between services, all communication is event-driven or in the form of data replication. This tends to form silos: independent services that are fed all the data they need by an async mechanism and can function independently of any…
Our microservice stack (opens on the source site)
This is an introduction to how we’ve implemented microservices at a mid-size scale-up called Jobteaser, with a mix of Go and Ruby service chassis, gRPC APIs and data replication via Kafka.Foundation: The service chassisBack in early 2019, when Jobteaser decided to get serious about breaking up its decade-old Rails monolith into microservices, we assembled a Foundation team that started working on an in-house service chassis.It was soberly coined service and came in two flavours: the rb-service framework in Ruby and the go-service framework in Go. Four years later, they still form the…
A Taste of Pakora (opens on the source site)
Strava ·
My name is Avery Dunn and I am a rising master’s student at Washington University in St. Louis studying computer science. For the past 12 weeks, I have been a software engineering intern on the API & Platform pod of the Foundation team. I am an active Strava user and have been for approximately 3 years with my favorite activity being running. Some other activities I enjoy are playing the piano, reading novels, or skiing (more of a luxury rather than a hobby). My internship at Strava has been a wonderful experience to help me learn, grow, and develop into becoming a more well-rounded,…
The End of the Public API Strangler (opens on the source site)
This is the story of how we used the Strangler pattern to migrate our public API from a monolithic codebase to a fully fledged BFF over the…
Service Architecture at SoundCloud — Part 3: Domain Gateways (opens on the source site)
This article is the last part in a series of posts aiming to cast some light onto how service architecture has evolved at SoundCloud over…
Are you sure microservices architecture is for you? (opens on the source site)
Today is the starting of the fourth year since I began my journey with microservices. I started with a theoretical knowledge about this architecture and now I ended up with a more deep and practical experience. While I still believe I can find news problems in microservices, I prepared an article with a list of problems which I had a chance to face in my work. You will read short stories which I faced during my work. If you don’t agree with them and think that they could be fixed and identified earlier - that’s okay, I believe that you can’t find a microservices structure with identical…
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This page is generated automatically from the engineering blogs we follow. Every post links to its source, where it was published. See all sources.