These are my notes from the Thoughtworks meetup on Nov 23rd 2022 (link contains recording) with Marion Bruns and Rahul Punjabi about platform monoliths and why you should avoid them.

Why you should avoid platform monoliths

Some background

  • platform as enabler for enterprises to deliver customer value quickly
    • in this talk, focus on developer platform
  • why invest?
    • t2market, cost efficiency, reliabilit, security
  • reality check for dev platforms

    “have you faced one or more of these challenges?”

    • platform becomes a bottleneck
    • low adoption rate amongst developers
    • insufficient performance
    • new features take long time to be implemented
    • costs are rising

online poll reveals: “some of the points above applied to 57% of the audience”

Why do platforms fail?

  • treating the cloud like on-prem DCs
    • delegated to a team that previously maintained the on-prem DC
    • ticket-based
    • silos
    • no interaction with outer world
    • no product thinking
    • “it takes more to enable autonomous teams and the business value you want to achieve”
  • not planning for right scale
    • scaling up AND scaling down (starting with tons of resources, not really required)
  • assuming what platform customers want
    • “we wil build something and they will come” -> does not really happen
    • lack of collaboration with future customers
    • lack of product thinking
  • unbalanced capabilities across teams
    • things get developed in isolation
    • when times come, devs need to be onboarded without proper capabilities
    • platform tends to be too complex

Traditional drivers: monolithic platform formula

seen by a lot of clients, when first approaching TW)

  • what do we mean by that?
    • “platform team box in the cloud”
      • users and access key, IAM, CI/CD, networking, logging, monitoring
      • compute orchestrator (K8S or EC2 instances)
      • “if you want DevOps, Jenkins is probably the first step”
      • underlaying: runtime cluster of nodes
      • service mesh in the middle between cluster and customer workload… service discovery, circuit breaking, service2service comm…
      • client workload running on top, eventually “soft” isolation of workloads
    • issue with service mesh - ask: do you really need that? only makes sense with micro services at scale
      • often get implemented without actual need, very complex
      • service meshes can slow down entire architecture
    • last but not least: data as the most sensitive asset of your company
      • data is part of the “platform box” - data is sitting there… customer data, product data, potentially highly confidential
      • sits in the same box that is accessible by everybody
  • there are some use cases where this box-approach can work
    • but many times, this approach does not work
  • centralized platform IS NOT a sensible default
    • security
    • reliability
    • maintainability
    • performance

Why is the this monolithic platform formula NOT a sensible default

  • security incidents
    • ask: “when and how they might happen” not “if they may happen”
    • think about the attack surface, how might an attacker attack the platform
    • what permissions do your roles allow?
    • how and where is your data stored - how granular are permissions to data…
  • share multi-purpose platform
    • one container orchestrator vs. workloads of varying characteristics that should run on the platform
      • example: one CI/CD system for all customers, but runners might have completely different characteristics in terms of platform requirements
    • capacity management
      • despite automated measures in the container orchestrators, you will be flooded with requests for fixing resource issues
    • you lose the capabilities of modern cloud in terms of scalability…
  • Cluster administration with an enormous failure radius
    • how much effort do you have to put into patching and upgrading
    • what about the likelihood that an individual workload can block your cluster from udpating appropriately
    • what about your confidence in recovering from cluster-wider failures?
  • Multi-tenancy limitations
    • maintaining multi-tenancy on compute, storage and network is complex
    • there are a lot of measures that can be taken & provided by cloud provider, but implementing them can become very tedious
    • you easily run into an amount of policies that are hard to maintain on a platform level
    • limitations in network resources (IPv4 addresses, ports…)

What are the solutions at hand?

What can we learn from Microservices, Data Mesh & Evolutionary Architecture (applied to developer platforms)

  • Architectural Quantum
    • independently deployable component with high functional cohesion, required by system to function properly

Formula for the design of a decentralized platform

  • Dedicated architectural quantum for each customer
    • Azure: one subscription for each customer
  • what’s inside
    • compute
    • network integration
    • observability tooling
    • IMPORTANT: capabilities depend on your use case
  • how is this benefitial
    • security incident: fix it for one affected customer
    • setup auto-scaling suitable for the one workload / use case of customer
    • you won’t run out of resources for an individual customer (as long as cloud provider can offer more)
    • you can apply horizontal scaling (if needed)
  • shared services in platform
    • hybrid networking
    • inter-quantum networking
    • internet connectivity
    • DNS and service discovery
    • compliance automation (making sure, users follows policies)
  • platform services (will vary from context to context - this is just a spectrum)
    • IaC and pipelines for infrastructure management
    • compliance and government policies
    • developer portal
    • community forum
  • we encourage to put as many capabilities as possible in the quantum, since it is still managed by the platform team

  • Outcomes of running decentralized platforms at scale
    • applied to multiple public cloud providers - approach worked for multiple clouds
    • how long does it take: productive customers within the year of inception
    • allows for self-service for the teams
    • allows for security guard rails
    • increased cost-transparency

Core capabilities and practices for successful platform strategies

  • it’s more than just implementation - eg. balance capabilities across teams - how do I approach in a way that everyone can benefit from it

  • Product Thinking
    • do user research, get requirements from your customers, do enough research to get those requirements
    • Define measures of success - you have to do this right from the start - are you helping your customers or are you getting in their way?
    • product strategy - product owner who can aling with business objectives - have a platform to serve the business objectives
    • establish and communicate service level objectives
  • shared responsibility
    • mapping technical capabilities and interfaces (interfaces in terms of “how do you collaborate”)
    • what does it mean to define technical capabilities
      • define collboratively the needed tech capabilities
      • define model on how you offer capabilities (just documentation, code snippets, …)
      • define the interaction model with the development teams (self-service, developer portal, …) - but even close collaboration with the dev team
      • how do you want to onboard? you might even need to go into the team(s) and help them with onboarding
  • self-service
    • invest in a developer portal (eg. Backstage)
      • step-by-step guide in how developers can make use of services
      • there should be no need for devs to write tickets to get something (onboarding new user, new VM…)
    • build automated, dev friendly interfaces
    • provide paved paths for frequent user journeys
    • build in quality gates and guardrails
  • Lightweight governance
    • enable autonomous teams!
    • treat principles and guardrails as living artifacts
    • use compliance as code and automation to enforce them
    • continuously collaboration on those principles - allow for users to work and aling on these principles - collaboration is key

Some of the challenges

  • Isn’t this more expensive?
    • return question: how are you looking at costs?
    • consider hollistic view of costs over local optimization
    • when slowing down customers with monolithic platform eg., experimentation, platform reduces competitive advantages of your dev teams
  • Orchestration of dependencies across platform infrastructure

  • Balancing infra capabilities across platform and customer teams (especially when starting with the platform)


  • monolithic platforms can restrict its own evolution and restric the customers

References & resources