Intro to Knative

Sep 17, 2018Download as PPTX, PDF12 likes2,017 views

Knative builds on Kubernetes and Istio to provide "PaaS-like abstractions" that raise the level of abstraction for specifying, running, and modifying applications. Knative includes building blocks like Knative Serving for autoscaling container workloads to zero, Knative Eventing for composing event-driven services, Knative Build for building containers from source, and Knative Pipelines for abstracting CI/CD pipelines. While Knative can run any type of container, its building blocks help enable serverless-style functions by allowing compute resources to scale to zero and be driven by event loads.

Christian Posta
Chief Architect, cloud application development
Twitter: @christianposta
Blog: http://blog.christianposta.com
Slides: http://slideshare.net/ceposta
• Author “Microservices for Java developers”
and “Introducing Istio Service Mesh”
• Committer/contributor lots of open-source projects
• Blogger, speaker, mentor, leader

Kubernetes
Established primitives for deploying and managing
container workloads at scale

Istio
How workloads interact with each other over
the network in a secure, reliable, observable way

Knative
“PaaS” like abstractions on top of Kubernetes that
leverage Istio and raise the level of abstraction for
specifying, running, and modifying applications

Well… WTF is “serverless”?
@christianposta

@christianposta
Serverless: outsourcing core infrastructure services to
cloud providers and stitching it all together through APIs
(and functions) to deliver business value

Service Full?
https://www.slideshare.net/jedi4ever/from-serverless-to-service-full-how-the-role-of-devops-is-evolving

● Per-request billing / pay as you go
● Typically accessed via APIs
● You don’t own it or care how it’s implemented
● Agreed SLAs
● Explicit choice, with tradeoffs, to not own the technology to
run your business
Service-full

● New, smaller unit of compute
● Executed on demand, typically in response to events
● Used to glue together APIs, services
● Concurrency, scale, spin up/spin down, etc done by platform
● High utilization rates (wrt billing – pay for what you use)
Functions (FaaS)

● Agility
● Flexibility (opinionatedness)
● Cost/utilization
● Technology ownership
● Complexity
Tradeoffs across these (at least spectrums):

When to use Serverless, Functions,
Microservices, Monoliths?
@christianposta
^^^ Save this for after 

Knative is building blocks for a PaaS
@christianposta

Knative operates on containers. Those
containers can be anything. Can they be
functions? Can you build FaaS on Knative?
@christianposta

Let’s take a look at one of the “building
blocks”…
@christianposta

Let’s take a look at these building blocks
@christianposta

Knative Serving: Allow our compute utilization
to be driven by request load (think:
autoscaler)
and scale to zero when no load

Knative Eventing: Composing services and
compute resources via events to build staged
event driven architectures

Knative Build: Converting source packages
into runnable containers

Knative Pipelines: Leverage Knative Build and
Knative Events to abstract away CI/CD
implementations on top of Kubernetes

Knative Caching: Simple API for providing
caching to Knative components (TBD - still
being sorted out).

Those most mature of the building blocks is
Knative serving
@christianposta

Thanks!
BTW: Hand drawn diagrams made with Paper by FiftyThree.com 
Twitter: @christianposta
Blog: http://blog.christianposta.com
Email: christian@redhat.com
Slides: http://slideshare.net/cepostaFollow up links:
• http://blog.christianposta.com
• http://istio.io
• http://envoyproxy.io
• http://linkerd.io
• http://consul.io
• http://bit.ly/istio-tutorial
• http://blog.christianposta.com/istio-workshop/slides/

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Microservices have been great for accelerating the software innovation and delivery, but they also present new challenges, especially as abstractions and automated orchestration at every layer make pinpointing the issue seem like walking around a maze with a blindfold. Existing tools weren’t designed for distributed environments, and the new tools need to consider how to leverage these abstraction layers to better observe, test, and troubleshoot issues. Christian Posta walks you through Envoy Proxy and service mesh architecture for L7 data plane, the key features in Envoy that can help in debugging and troubleshooting, chaos engineering as a testing methodology for microservices, how to approach a testing and debugging framework for microservices, and new open source tools that address these areas. You’ll explore a workflow to discover and resolve microservices issues, including injecting experiments for stress testing the applications, gathering requests in flight, recording and replaying them, and debugging them step by step without affecting production traffic.

Kubernetes Ingress to Service Mesh (and beyond!)Christian Posta

Kubernetes users need to allow traffic to flow into and within the cluster. Treating the application traffic separately from the business logic allows presents new possibilities in how service to service traffic is served, controlled and observed — and provides a transition to intra cluster networking like Service Mesh. With microservices, there is a concept of both North / South traffic (incoming requests from end users to the cluster) and East / West (intra cluster) communication between the services. In this talk we will explain how Envoy Proxy works in Kubernetes as a proxy for both of these traffic directions and how it can be leveraged to do things like traffic shaping, security, and integrate the north/south to east/west behavior. Christian Posta (@christianposta) is Global Field CTO at Solo.io, former Chief Architect at Red Hat, and well known in the community for being an author (Istio in Action, Manning, Istio Service Mesh, O'Reilly 2018, Microservices for Java Developers, O’Reilly 2016), frequent blogger, speaker, open-source enthusiast and committer on various open-source projects including Istio, Kubernetes, and many others. Christian has spent time at both enterprises as well as web-scale companies and now helps companies create and deploy large-scale, cloud-native resilient, distributed architectures. He enjoys mentoring, training and leading teams to be successful with distributed systems concepts, microservices, devops, and cloud-native application design.

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The exploration of service mesh for any organization comes with some serious questions. What data plane should I use? How does this tie in with my existing API infrastructure? What kind of overhead do sidecar proxies demand? As I've seen in my work with various organizations over the years "if you have a successful microservices deployment, then you have a service mesh whether it’s explicitly optimized as one or not." In this talk, we seek to understand the role of the data plane and how to pick the right component for the problem context. We start off by establishing the spectrum of data-plane components from shared gateways to in-code libraries with service proxies being along that spectrum. We clearly identify which scenarios would benefit from which part of the data-plane spectrum and show how modern service meshes including Istio, Linkerd, and Consul enable these optimizations.

Deep Dive: Building external auth plugins for Gloo EnterpriseChristian Posta

Role of edge gateways in relation to service mesh adoptionChristian Posta

API Gateways provide functionality like rate limiting, authentication, request routing, reporting, and more. If you’ve been following the rise in service-mesh technologies, you’ll notice there is a lot of overlap with API Gateways when solving some of the challenges of microservices. If service mesh can solve these same problems, you may wonder whether you really need a dedicated API Gateway solution? The reality is there is some nuance in the problems solved at the edge (API Gateway) compared to service-to-service communication (service mesh) within a cluster. But with the evolution of cluster-deployment patterns, these nuances are becoming less important. What’s more important is that the API Gateway is evolving to live at a layer above service mesh and not directly overlapping with it. In other words, API Gateways are evolving to solve application-level concerns like aggregation, transformation, and deeper context and content-based routing as well as fitting into a more self-service, GitOps style workflow. In this talk we put aside the “API Gateway” infrastructure as we know it today and go back to first principles with the “API Gateway pattern” and revisit the real problems we’re trying to solve. Then we’ll discuss pros and cons of alternative ways to implement the API Gateway pattern and finally look at open source projects like Envoy, Kubernetes, and GraphQL to see how the “API Gateway pattern” actually becomes the API for our applications while coexisting nicely with a service mesh (if you adopt a service mesh).

Navigating the service mesh landscape with Istio, Consul Connect, and LinkerdChristian Posta

The document discusses various service mesh options including Linkerd, Consul Connect, Istio, and AWS App Mesh. It provides an overview of each solution, describing their key features and strengths/opportunities. It emphasizes that the service mesh approach is useful for managing inter-service communication and that implementations are still evolving. It recommends starting simply and iteratively adopting capabilities to match needs.

Chaos Debugging for MicroservicesChristian Posta

Distributed microservices introduce new challenges: failure modes are harder to anticipate and resolve. In this session, we present a “Chaos Debugging” framework enabled by three open source projects: Gloo Shot, Squash, and Loop to help you increase your microservices’ “immunity” to issues. Gloo Shot integrates with any service mesh to implement advanced, realistic chaos experiments. Squash connects powerful and mature debuggers (gdb, dlv, java debugging) to your microservices while they run in Kubernetes. Loop extends the capability of your service mesh to observe your application and record full transactions for sandboxed replay and debugging. Come to this demo-heavy talk to see how together, Squash, Gloo Shot, and Loop allow you to trigger, replay, and investigate failure modes of your microservices in a language agnostic and efficient manner without requiring any changes to your code.

Leveraging Envoy Proxy and GraphQL to Lower the Risk of Monolith to Microserv...Christian Posta

If you have an existing Java monolith, you know you must take care making changes to it or altering it in any negative way. Often times these monoliths are very valuable to the business and generate a lot of revenue. At the same time, since it’s difficult to make changes to the monolith it’s desirable to move to a microservices architecture. Unfortunately you cannot just do a big-bang migration to a greenfield architecture and will have to incrementally adopt microservices. In this talk, we’ll look at using Gloo proxy which is based on Envoy Proxy and GraphQL to do surgical, function-level traffic control and API aggregation to safely migrate your monolith to microservices and serverless functions.

Service-mesh options with Linkerd, Consul, Istio and AWS AppMeshChristian Posta

Service mesh abstracts the network from developers to solve three main pain points: How do services communicate securely with one another How can services implement network resilience When things go wrong, can we identify what and why Service mesh implementations usually follow a similar architecture: traffic flows through control points between services (usually service proxies deployed as sidecar processes) while an out-of-band set of nodes is responsible for defining the behavior and management of the control points. This loosely breaks out into an architecture of a "data plane" through which requests flow and a "control plane" for managing a service mesh. Different service mesh implementations use different data planes depending on their use cases and familiarity with particular technology. The control plane implementations vary between service-mesh implementations as well. In this talk, we'll take a look at three different control plane implementations with Istio, Linkerd and Consul, their strengths, and their specific tradeoffs to see how they chose to solve each of the three pain points from above. We can use this information to make choices about a service mesh or to inform our journey if we choose to build a control plane ourselves.

Intro Istio and what's new Istio 1.1Christian Posta

The document summarizes the new features of Istio 1.1, an open-source service mesh. Some key highlights include improved performance and scalability, namespace isolation, multi-cluster capabilities, easier installation with Helm, and locality-aware load balancing. A new Sidecar resource was introduced to improve performance by configuring resources for individual proxies. The presentation demonstrates performance improvements with the Sidecar resource and highlights additional functionality in Istio like traffic control and metrics collection.

API Gateways are going through an identity crisisChristian Posta

API Gateways provide functionality like rate limiting, authentication, request routing, reporting, and more. If you've been following the rise in service-mesh technologies, you'll notice there is a lot of overlap with API Gateways when solving some of the challenges of microservices. If service mesh can solve these same problems, you may wonder whether you really need a dedicated API Gateway solution? The reality is there is some nuance in the problems solved at the edge (API Gateway) compared to service-to-service communication (service mesh) within a cluster. But with the evolution of cluster-deployment patterns, these nuances are becoming less important. What's more important is that the API Gateway is evolving to live at a layer above service mesh and not directly overlapping with it. In other words, API Gateways are evolving to solve application-level concerns like aggregation, transformation, and deeper context and content-based routing as well as fitting into a more self-service, GitOps style workflow. In this talk we put aside the "API Gateway" infrastructure as we know it today and go back to first principles with the "API Gateway pattern" and revisit the real problems we're trying to solve. Then we'll discuss pros and cons of alternative ways to implement the API Gateway pattern and finally look at open source projects like Envoy, Kubernetes, and GraphQL to see how the "API Gateway pattern" actually becomes the API for our applications while coexisting nicely with a service mesh (if you adopt a service mesh).

Making sense of microservices, service mesh, and serverlessChristian Posta

What Istio Got Wrong: Learnings from the last seven years of service meshChristian Posta

Move Auth, Policy, and Resilience to the PlatformChristian Posta

Comparing Sidecar-less Service Mesh from Cilium and IstioChristian Posta

Understanding Wireguard, TLS and Workload IdentityChristian Posta

Compliance and Zero Trust Ambient MeshChristian Posta

Cilium + Istio with Gloo MeshChristian Posta

Multi-cluster service mesh with GlooMeshChristian Posta

Multicluster Kubernetes and Service Mesh PatternsChristian Posta

Cloud-Native Application Debugging with Envoy and Service MeshChristian Posta

Kubernetes Ingress to Service Mesh (and beyond!)Christian Posta

The Truth About the Service Mesh Data PlaneChristian Posta

Deep Dive: Building external auth plugins for Gloo EnterpriseChristian Posta

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Navigating the service mesh landscape with Istio, Consul Connect, and LinkerdChristian Posta

Chaos Debugging for MicroservicesChristian Posta

Leveraging Envoy Proxy and GraphQL to Lower the Risk of Monolith to Microserv...Christian Posta

Service-mesh options with Linkerd, Consul, Istio and AWS AppMeshChristian Posta

Intro Istio and what's new Istio 1.1Christian Posta

API Gateways are going through an identity crisisChristian Posta

Making sense of microservices, service mesh, and serverlessChristian Posta

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