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Rohit leads the Pivotal Labs App Modernization Practice in engineering, delivery training & cross-functional enablement, tooling, scoping, selling, recruiting, marketing, blog posts, webinars and conference sessions. Rohit has led multiple enterprise engagements including ones featured in the Wall Street Journal. Rohit focuses on designing, implementing and consulting with enterprise software solutions for Fortune 500 companies on application migration and modernization.

Saturday, August 1, 2020

Designing Good APIs

Part 1 -- Principles of Designing & Developing APIs (for Product Managers, Product Designers, and Developers)

Part 2 -- Process of Designing APIs (for Product Managers, Product Designers, and Developers)

Part 3 -- Tips for managing an API backlog (for Non-Technical PMs)

Part 4 -- Developing, Architecting, Testing, & Documenting an API (for Developers)

API First Development Recipe

How To Document APIs

Shopify APIs

API Design 

Friday, July 24, 2020

Don't Use Netflix Eureka For Service Discovery

So  … there are multiple issues with Eureka
  1. Deprecated by Netflix and no longer maintained by Pivotal/VMware.  So no long term future maintainer.
  2. The whole world seems to have moved on to either the service discovery provided natively by the platform like Kube DNS (Kubernetes) or Bosh DNS (Cloud Foundry) or service meshes (Istio) or service networking product like Consul.  See replacing-netflix-eureka-with-kubernetes-services and polyglot-service-discovery-container-networking-cloud-foundry 
  3. Eureka does not work with Container to Container networking
  4. Stale Service Registry Problem - Eureka & Ribbon don’t react quickly enough to apps coming up and down due to aggressive caching see making-service-discovery-responsive

Monday, June 22, 2020

The Eight Factors of Cloud Native Gemfire Applications

If after moving the in memory JVM cache to Gemfire your pain still hasn't gone away take a look at this checklist of factors for getting you app to perform efficiently with Gemfire. Thanks to my buddy Jeff Ellin who is a expert ninja at Gemfire and PCC.


Look at queries and data. If you have a read problem then the query is not constructed correctly or the data is not partitioned correctly. If its a write problem it's probably a cluster tuning issue, network issue or some bad synchronous listeners that have been implemented. The best way to triage this is to  take some stats files you can be loaded up into vsd. Gemfire keeps a lot of statistics you can visualize. You can see throughput of various operations.

Here are some of the other things you should probably look at.
  1. Data Partitioning 
  2. Non index lookups 
  3. Serialization 
  4. Querying on the server they should be using PDX for OQL Queries. If you aren’t using PDX the server needs to deserialize the object to do the query. Any time you query for data that isn’t the key you are using OQL 
  5. Data Colocation strategy of data (customer orders should be on the same partition as customer record, reference data should be replicated) 
  6. Leveraging Transactions Incorrectly (all objects must be in the same partition). Make your operations idempotent instead of relying on transactions. 
  7. Excessive GC activity due to data changing too frequently. 
  8. If networking sucks performance will suck due to the amount of replication - In rare cases you may need to enable Delta Propagation if the objects being serialized are big . also read When to avoid delta propogation. For each region where you are using delta propagation, choose whether to enable cloning using the delta propagation property cloning-enabled. Cloning is disabled by default. See Delta Propagation PropertiesIf you do not enable cloning, review all associated listener code for dependencies on EntryEvent.getOldValue. Without cloning, GemFire modifies the entry in place and so loses its reference to the old value. For delta events, the EntryEvent methods getOldValue and getNewValue both return the new value.

Thursday, June 18, 2020

2020 A Year In Review

  • Leading the delivery of  one-of-a kind Application Modernization Navigator   of a Pharmacy Benefits Management system currently running in the mainframe.
  • Led the first two Remote Application Swift Navigators creating the Playbook for Remote Event Storming and other remote collaborative modeling practices.
  • GoToMarket Remote App Modernization Navigators https://tanzu.vmware.com/content/resources-for-remote-software-teams/how-to-conduct-a-remote-event-storming-session
  • Self Published Book on Practical Microservices 
  • Self Published Book on Emergent Trends on Modern Applications 
  • Improving the quality and number of recipes in our App Modernization Cookbooks and opening our tools like SNAP to broader VMware commnunity.
  • One of the lead Influencers in MAPBU Services Marketing measured in Published articles and blog posts, internal documents and views
  • Top articles including How to Build Sustainable, Modern Application Architectures https://tanzu.vmware.com/content/practitioners-blog/how-to-build-sustainable-modern-application-architectures
  • CKA and CKAD Certified in 2019. Conducted training for both Labs and class AppTx App Services on How to get certified on Kubernetes.
  • Taught broader MAPBU organization on How To  Conduct Remote Scopings. 
  • Taught Multiple (> 5) Swift Modernization Workshops across Pivotal and VMware for Scaling App Modernization
  • Working with R&D to bring Spring Transformation Tooling to market. Created Spring Bootifier with Tim Dalsing which is now used in the implementation of Tanzu Workbench Spring Bootifier Transformer. Currently aligning with Spring R&D effort on automated cloud native remediation of Java applications.
  • Created Kafka battle-card for App Services sales 
  • Anchored One Off a Kind Kafka  Real Time Inventory Engagement and created collateral for App Modernization For Streaming workloads deck 
  • Creating App Services pipeline at our top customers - Over 375+ individual Travelers participants attended the Should This Be A Microservice webinar on Tanzu enablement see  Over 2500 views on linkedin.
  • COVID 19 Project - Facilitator of Remote Swift Event Storm and Boris exercises. This client is a small startup who worked with Labs Seattle 4 years ago on an app to connect in home carers with medicaid recipients. Since COVID 19 they've expanded their platform to now connect essential workers with childcare providers. They're experiencing a huge demand for this service. Unsurprisingly, there is a huge demand for this service. They are currently rolling out to public hospitals in LA.
  • Working across discovery teams to formulate the Discovery scoping and workshop process. 

Tuesday, June 2, 2020

Modernization Myths - Microservices - Explained

Myth - “Microservices Is The Only True Way”

Why are microservices the default way of developing cloud native applications ? Why does application Modernization in the form of decomposing monoliths result in so many microservices ? Why has microservices become the default deployment model for applications in spite of enterprises struggling with the observability, complexity and performance of the distributed system. Heisenbugs abound when you mix sync and async flows further compounded by various forms of async event driven architecture like thin events, thick events, event sourcing, CQRS etc.,
Frustrated by the intractability and cognitive overload of monoliths, I  was one of the first people to ride the monoliths to the microservices wave. However six years after the Microservices article came out from Martin Fowler and James Lewis came out, it is time to retrospect on reality. Have Microservices got you down ? Are you swimming in a mess of brittle microservices that break every night ? Are the number of microservices going up resembling the death-star architecture ? It behooves us to travel upstream and examine the motivations for microservices. How do we peel back the onion and get back to sanity around microservices. How do we rationalize microservices ?
So what is the path forward ? Throw the baby out of the bathwater and swing back to Monoliths. There ought to be a middle way where we can take best of the microservices advantages like domain based composition, enforced module boundaries, independent evolvability, better cognition etc.  It is time to look after life after running microservices architectures in production and learn from the mistakes committed over the past five years.
There is a way that has emerged from working with a number of customers where the value of microservices has not been realized from application modernization despite leveraging Domain Driven Design and doing all things right. This process adds sanity to the process of constructing microservices and provides guidelines and design heuristics on structuring microservices. We need to tackle this problem from a technical, business and social perspective marrying concepts from DDD with Wardley Business Maps and Sociotechnical architecture. Rationalize microservices into modular monoliths based on technical and business heuristics. Employ techniques  which are  a combination of mapping microservices to core technical attributes reduced by affinity mapping and business domain context distillation. This workshop/process called micro2monp has simplified enterprise architectures and improved the operational burden of microservices. You can find more details of the process here and six-factors and post

So How DO you Rationalize your microservices ?  Here is a presentation that walks through all the factors that should be used for rationalizing Microservices.

A Blueprint For Mainframe Modernization

At VMware Pivotal Labs we have cracked the code of Mainframe Modernization. Frustrated with low fidelity code generators migrating COBOL to Java, losing business rules in the process ?. Tired of multi-year modernization projects with no end in sight. Take a look at the seven step punch VMware Pivotal employs to achieve concrete modernization business outcomes for high value critical mainframe OS400 and OS390 workloads.

Modernization in weeks not months and years
Blueprint For Mainframe Modernization VMWare Pivotal Labs

Monday, June 1, 2020

Explain VMware Tanzu To Me Like I am Eight

Me breaking down the VMware Tanzu Portfolio suite with my son Rushil Kelapure.

Modernizing applications feels like an overwhelming job. Maintaining dev and prod environment parity seems a Sisyphean task. Container builds vary wildly, creating snowflakes with every sprint. Even new, promising runtimes that come along face fragmentation as different teams adopt different versions. With a consistent approach, however, the layers between infrastructure and application code become manageable. VMware Tanzu portfolio, brings consistency to building, running, and managing code. VMware is the only company that addresses the challenges of application modernization from both the application and the infrastructure perspective.

Tuesday, May 26, 2020

Modernization Myths Explained 1 & 2

In this blog post we go deeper into the top two myths of Application Modernization. An overview of all the top 10 myths can be found here

Myth 1 - “Application has to be cloud native to land on a PaaS”

The truth is that most Platforms As A Service run applications of different cloud native characteristics just fine. Applications have to progress through a spectrum as they land and flourish in the cloud from Not running in the cloud, to running in the cloud, to running great in the cloud. A PaaS like Cloud Foundry has also evolved features like volume services and multi-port routing to help stateful and not born on the cloud applications run without changes on Cloud Foundry.  In his blog series  debunking Cloud Foundry myths , Richard Seroter authoritatively disproves the notion that  Cloud Foundry can only run cloud-native applications.
Applications do not have to be classic 12 factor or 15 factor compliant to land on PaaS. Applications evolve on the cloud native spectrum. The more cloud native idiomatic changes to an app - the more return on investment you get from the changes. The more cloud native you make the app, the higher the optionality you get since it becomes cloud agnostic allowing enterprises to exact maximum leverage from all the providers. The focus needs to be on the app inside-out to get the best returns. In general the higher you are in the abstraction stack the more performance gains you will get so Architecture changes will yield a 10x more benefit than JVM or GC tuning which will yield a 10x more benefit than tuning assembly code and so on … If it is the database tier that you think is the problem - then you can put in multiple shock absorbers instead of tuning the startup memory and app start times. Apps first, Platform second :-)  

Cloud Foundry Support For Stateful Applications
Myth 2 - “Application have to be refactored to run them on Kubernetes”
It's a fallacy that applications need to be modified by developers before landing them on Kubernetes. In fact an enterprise can get significant cost savings by migrating one factor apps to Kubernetes. A one factor app simply has the capability to restart with no harmful side-effects James Watters the cloud soothsayer has posed the question in the cloud-native podcast - Do you even have a 1-factor application ? 

Most business applications are not ready for refactoring but still want the cost advantages of running in the cloud.  For apps where the appetite for change is zero, starting  small, as in just restarting the application predictably i.e. making it one factor can make it run on a container platform like Kubernetes. As you shift to declarative automation and scheduling, you will want the app to restart  cleanly. There is an application-first movement of being able to do some basic automation of even your monolithic applications. Apps are the scarce commodity right now. With Kubernetes becoming more and more ubiquitous — All the application portfolios need a nano change mindset to adapt to the cloud.

Saturday, May 16, 2020

Top Ten Application Modernization Myths

Sometimes we tell little lies to ourselves. It is always good to take inventory of reality and introspect on what is true and what is not. Here are some of the little lies of application migration and modernization that I have observed over the last five years. 
  1. Application has to be 12/15 factors compliant to land on PaaS. Apps can be modified on the cloud native spectrum. The more cloud native idiomatic changes to an app - the more ROI you get from the changes. See Myth #1 "Cloud Foundry can only run cloud-native, 12-factor apps." - FALSE https://tanzu.vmware.com/content/blog/debunking-cloud-foundry-myths
  2. Applications need to be modified by developers before landing them on Kubernetes (TKG). In fact an enterprise can get significant cost savings by migrating one factor apps to Kubernetes. A one factor app simply has the capability to restart with no harmful side-effects See https://tanzu.vmware.com/content/intersect/vmware-tanzu-in-15-minutes Do you even have a 1-factor application?
  3. Once technical debt on an application becomes unsurmountable the only recourse is to rewrite it. Surgical strikes with an emphasis on understanding the core domain can lead to incremental modernization of the most valuable parts of a big critical legacy system. A FULL rewrite is not the only option.  See technical debt like financial debt https://tanzu.vmware.com/content/intersect/risk-profile-of-technical-debt and https://tanzu.vmware.com/content/webinars/may-6-tech-debt-audit-how-to-prioritize-and-reduce-the-tech-debt-that-matters-most
  4. There is a silver bullet for app migration. There is an increasing bevy of tools that have started promising a seamless migration of VMs to containers in the cloud. Remember in life nothing is free. You get what you put in. Migration is highly contextual and the OPEX and Developer efficiency returns are dependent on the workloads being ported. Migration of apps in VMs to Kubernetes stateful sets or automatic dockerization through buildpacks etc should be evaluated for the desired objectives of the Migration Project.
  5. Microservices and event driven architecture is ALWAYS the right architecture choice for app modernization. Sometimes the answer is to step back simplify the domain and implement a modular monolithic system and sometimes the answer is to decompose the large system into a combination of microservices and functions. Understand the design and operational tradeoffs first before making the choice. Every tech choice like eventing, APIs, streaming etc has a spectrum. The fundamental job of an architect is to understand the sociotechnical factors and make the right choices from a process, people and implementation perspective. see https://tanzu.vmware.com/content/practitioners-blog/how-to-build-sustainable-modern-application-architectures
  6. Decomposing and rearchitecture of an existing system can be done concurrently with forward development with little impact to exisrting release schedules. This is a dream. When working on two branches of an existing system a forward development branch and a rearchitecture branch > the total output often times gets worse before becoming better. WBB - This is because there is a period of time where dual maintenance and dual development and the coordination tax across two teams are levied without getting any of the benefits of modularization and refactoring. See The Capability Trap: Prevalence in Human Systems https://www.systemdynamics.org/assets/conferences/2017/proceed/papers/P1325.pdf https://rutraining.org/2016/05/02/dont-fall-into-the-capability-trap-does-your-organization-work-harder-or-smarter/
  7. The fundamental problems of app modernization are technical. If developers  only had the rigor and discipline to write idiomatic code all problems would be fixed and we won't incur technical debt. Wrong- The fundamental problems of app modernization are team and people related. Incorrect team structure, wrong alignment of resources to core domains and messed up interaction patterns are far more responsible for the snail pace for feature addition rather than technical changes. The answer is team re-organization based on the reverse conway maneuver. See Team Topologies https://www.slideshare.net/matthewskelton/team-topologies-how-and-why-to-design-your-teams-alldaydevops-2017
  8. Mainframe modernization can be accelerated by using lift-n-shift tools like emulators or code generation tools. In our experience a complex mainframe modernization almost always involves a fundamental rethink of the problem being solved and then rewriting a new system to address the core domain divorced from the bad parts of the existing intermingled complex system. Theory of constraints and a systems thinking help us reframe the system and implement a better simpler one.
  9. Engineers, Developers and Technical Architects tend to think from a technical nuts and bolts perspective (the “how”) and, therefore, tend to look at modern technologies such as Cloud Foundry, Spring Boot, Steeltoe, Kafka and containerization as the definition of a modern application. This misses the mark. The Swift Method pioneered by Pivotal  helps bridge the gap in understanding between the non-technical, top down, way of thinking and the technical, bottom up thought process.  The end result is an architecture that maps to the way the system “wants to behave” rather than one that is dictated by the software frameworks of du jour. 
  10. AWS or Azure or GKE/GCP etc provide an all encompassing suite of tools, services and platforms to enable and accelerate modernization and migration of workloads. While it is true that the major cloud providers have ALL the bells and whistles to migrate workloads, the economics of app modernization tend towards the app and not the platform. The more cloud native you make the app, the higher the optionality you get since it becomes cloud agnostic allowing enterprises to exact maximum leverage from all the providers. The focus needs to be on the app inside-out to get the best returns. In general the higher you are in the abstraction stack the more performance gains you will get so Architecture changes will yield a 10x more benefit than JVM or GC tuning which will yield a 10x more benefit than tuning assembly code and so on … If it is the database tier that you think is the problem - then you can put in multiple shock absorbers 1. caches 2. queues 3. partitioning first and focused on instead tuning the startup memory and app start times. Apps first, Platform second :-)  

Friday, April 24, 2020

Java Application Modernization Maturity Model

This is how I think about the Maturity Model for Java Transformers

1. Basic Containerization of Stateless apps to TKG - enabled by https://github.com/pivotal/kpack and Cloud Native Buildpacks. - Deploy with vanilla  manifests that maybe helmified   / Basic Containerization to TAS - Using TAS Buildpacks ... some apps require no changes when deploying with JavaBuildpack. **O changes.**

2. TKG - Basic Containerization of Stateful apps possibly using K8s Stateful sets or persistent volumes. / TAS - Extract state out like session replication or databases (not sure how to do this yet).   Some tools purport to do this. Like Google anthos and the POC the tracker team is working on. **Minimal changes.**

3. Invasive S-boot transformer - high vaule - high degree of change and difficulty. Thae automate the transformation recipes to cloud native. Bootifier ones as well simpler ones like boot 2 -> boot 3, XML -> Config Migration.  **Invasive changes.**

4. Microservice generator - looking at the dynamic runtime of the appllication. Determines seams and makes suggestions where apps can be decomposed and used as a starting point for Swift. **Monoliths2Microservices**