Tag Archives: Istio

Podcast – Dave Blakey of Snapt on Radically Different ADC

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Joining us this week is Dave Blakey, CEO and Co-Founder Snapt.

About Snapt

Snapt develops high-end solutions for application delivery. We provide load balancing, web acceleration, caching and security for critical services.

 Highlights

  • 1 min 28 sec: Introduction of Guest
  • 1 min 59 sec: Overview of Snapt
    • Software solution
  • 3 min 1 sec: New Approach to Firewalls and Load Balancers
    • Driven by customers with micro-services, containers, and dynamic needs
    • Fast scale and massive volume needs
    • Value is in quality of service and visibility into any anomaly
  • 7 min 28 sec: Engaging with DevOps teams for Customer interactions
    • Similar tools across multiple clouds and on-premises drives needs
    • 80% is visibility and 20% is scalability
    • Podcast – Honeycomb Observability
  • 13 min 09 sec: Kubernetes and Istio
    • Use cases remain the same independent of the technology
    • Difference is in the operations not the setup
    • Istio is an API for Snapt to plug into
  • 17 min 29 sec: How do you manage globally delivered application stack?
    • Have to go deep into app services to properly meet demand where needed
    • Immutable deployments?
  • 25 min 24 sec: Eliminate Complexity to Create Operational Opportunity
  • 26 min 29 sec: Corporate Culture Fit in Snapt Team
    • Built Snapt as they needed a product like Snapt
    • Feature and Complexity Creep
  • 28 min 48 sec: Does platform learn?
  • 31 min 20 sec: Lessons about system communication times
    • Lose 25% of audience per 1 second of website load time
  • 34 min 34 sec: Wrap-Up

Podcast Guest:  Dave Blakey, CEO and Co-Founder Snapt.

Dave Blakey founded Snapt in 2012 and currently serves as the company’s CEO.

Snapt now provides load balancing and acceleration to more than 10,000 clients in 50 countries. High-profile clients include NASA, Intel, and various other forward-thinking technology companies.

Today, Dave has evolved into a leading open-source software-defined networking thought leader, with deep domain expertise in high performance (carrier grade) network systems, management, and security solutions.

He is a passionate advocate for advancing South Africa’s start-up ecosystem and expanding the global presence of the country’s tech hub.

.IO! .IO! It’s off to a Service Mesh you should go [Gluecon 2017 notes]

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TL;DR: If you are containerizing your applications, you need to be aware of this “service mesh” architectural pattern to help manage your services.

Gluecon turned out to be all about a microservice concept called a “service mesh” which was being promoted by Buoyant with Linkerd and IBM/Google/Lyft with Istio.  This class of services is a natural evolution of the rush to microservices and something that I’ve written microservice technical architecture on TheNewStack about in the past.

servicemeshA service mesh is the result of having a dependency grid of microservices.  Since we’ve decoupled the application internally, we’ve created coupling between the services.  Hard coding those relationships causes serious failure risks so we need to have a service that intermediates the services.  This pattern has been widely socialized with this zipkin graphic (Srdan Srepfler’s microservice anatomy presentation)

IMHO, it’s healthy to find service mesh architecturally scary.

One of the hardest things about scaling software is managing the dependency graph.  This challenge is unavoidable from early days of Windows “DLL Hell” to the mixed joy/terror of working with Ruby Gem, Python Pip and Node.js NPM.  We get tremendous acceleration from using external modules and services, but we also pay a price to manage those dependencies.

For microservice and Cloud Native designs, the service mesh is that dependency management price tag.

A service mesh is not just a service injected between services.  It’s simplest function is to provide a reverse proxy so that multiple services can be consolidated under a single end-point.  That quickly leads to needing load balancers, discovery and encrypted back-end communication.  From there, we start thinking about circuit breaker patterns, advanced logging and A/B migrations.  Another important consideration is that service meshes are for internal services and not end-user facing, that means layers of load balancers.

It’s easy to see how a service mesh becomes a very critical infrastructure component.

If you are working your way through containerization then these may seem like very advanced concepts that you can postpone learning.  That blissful state will not last for long and I highly suggest being aware of the pattern before your development teams start writing their own versions of this complex abstraction layer.  Don’t assume this is a development concern: the service mesh is deeply tied to infrastructure and operations.

The service mesh is one of those tricky dev/ops intersections and should be discussed jointly.

Has your team been working with a service mesh?  We’d love to hear your stories about it!

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