ServiceMeshCon North America 2021

The Linux kernel is an ideal place to implement observation, networking, and security, and improvements in the eBPF space are making it more practical to leverage the Linux kernel for these use-cases. Given that both eBPF and service mesh essentially allows users to program policies to connect, secure, and observe; you may be wondering how service mesh and eBPF intersect? This talk will explore different approaches to supercharge your service mesh with eBPF to make service mesh more secure and efficient.

Infrastructure diversity is a reality for many organizations. It’s predicted that by 2022, 90% of all apps will feature microservices architectures. A huge range of microservice patterns drives a world of multiple service meshes. As various service meshes have proliferated infrastructures, service mesh patterns and abstractions have emerged. We will break down 60 service mesh patterns into different categories of use, demonstrating and examining a select few using Meshery for deeper review of their problems they solve, discussing caveats, and highlighting anti-patterns. The patterns discussed are being published in Service Mesh Patterns (O’Reilly) by Lee Calcote and Nic Jackson.

Service meshes provides a wide range of capabilities including flexible configuration, high fidelity observability, and is transparent to user applications. However, this power, despite it's (often) open-source nature, does not come cheap. In the age of public cloud, vendors typically charge users on several axes of usage. When using a feature like traffic shaping, if not careful, cross-availability-zone traffic can quickly increase spend. High fidelity metrics are useful to operators, but default service mesh configurations can easily overwhelm systems, and users too. Suboptimal defaults coupled with user-local dashboards leads to high cardinality metrics further increasing costs of metrics storage solutions. Yet another area of spend is access logging. While being extremely important to diagnose runtime issues, access logs can quickly become a $$$ drain. The default policy of logging each request is not the best configuration for most users, and organizations need to craft these policies based on their unique environments. In this talk, we will talk about costs we've encountered when using a service mesh at scale at Stripe. We will also discuss some strategies we have in place for reducing spend, and other techniques to improve the overall experience with service meshes.

Service mesh is an infrastructure layer for micro services. It provides functions like: service discovery, traffic routing/shifting, security, observability etc. Multi-tenant is very common in kubernetes clusters. So how to better utilize service mesh capabilities while providing enterprise multi-tenant support in kubernetes clusters? In this talk we will walk you through below items and show you some tradeoffs for different service mesh options. 1. What challenges does multi-tenant bring to Service Mesh? 2. What service mesh options are applicable for multi-tenant support? 3. What does single mesh and multi mesh mean for multi-tenant and what are their Cons & Pros? 4. Performance comparison for different service mesh topology on multi-tenant clusters.

To increase the pace of feature iteration and reduce costs, Elkjøp, the largest electronics retailer in the Nordics, migrated their application from Azure App Service to Kubernetes and Linkerd. In this talk, Fredrik describes how they built the new platform while rapidly onboarding themselves and their developers onto both Kubernetes and service mesh expertise, and how they addressed the concerns of their developer managers, who were happy with the status quo and uneasy about the proposed change.

SAP has embarked on a journey to design and implement multi-cluster “Service Mesh as a Service” for its BTP platform.They did not stop there though, they aim to connect these meshes together in a “mesh of meshes” architecture. Fei Yao, Chief Architect at SAP will talk about the challenges and design patterns (with help from Nick Nellis at Solo.io) that are helping enable SAP to connect and manage service meshes for 40,000 engineers and over 10,000 clusters.

A service mesh is a critical piece of application infrastructure that lives on the request path between your services. Once you get past the “hello world” for your particular mesh, you are left having to plan out your production deployment and more importantly, future upgrades. The architecture and patterns for deployment are as important (if not more?) as the specific mesh capabilities you choose. For example, patterns like separating ingress, running canaries, and focusing on limited configuration blast radius are foundational to enable zero-downtime upgrades of your mesh. In this talk, we discuss the vital patterns and practices cultivated working with mesh adopters around the world. The audience should come away with a core set of practices to enable successful lifecycle management of their service mesh.

Multi-cloud strategy is becoming the new norm when it comes to cloud adoption for enterprises, especially for global companies cross multiple geographic regions. Many factors can contribute to the motivation behind multi-cloud strategy, including best of the class solutions from multiple cloud providers, reliability and flexibility, and optimal performance-cost benefits. All major cloud providers are offering coherent solutions to enable hybrid and multi-cloud strategies. Among all solutions, Service Mesh is an effective technology to deliver the benefits of multi-cloud strategy to enterprises. We will examine a few multi-cloud use cases and architecture considerations and how to leverage service mesh for typical enterprise multi-cloud strategies, including failover, best of class, and flexible scale-in-and-out application deployment patterns. In particular, we will explore private connections among multiple cloud providers to ensure enterprises the ultimate security and privacy for their data while enabling multi-cloud strategies.