The Rise of Nomad in Cloud Workload Management

Introduction

Anyone could think that the DevOps community had already settled the debate of the best workload orchestrator for the cloud, with Kubernetes emerging as the clear winner and becoming the industry standard. However, a particular project has been gaining popularity in recent years because of its different approach to orchestration and scheduling, addressing some gaps in the field. That project is Nomad, an open-source workload orchestrator developed by HashiCorp, the creators of other well-known tools like Terraform, Packer, Consul, and Vault.

In this blog, we will dive into what Nomad is, its key features, and how it differentiates itself from other, more established orchestrators in the market, such as Kubernetes. In future blogs, we’ll explore a hands-on, setting up a local dev environment for Nomad to test its features. Before we proceed, let’s take a moment to clarify two crucial terms that will lay the groundwork for our discussion: the definition of an orchestrator and the meaning of a workload.

Orchestrator

An orchestrator is a program that coordinates and schedules complex tasks across an infrastructure. The orchestrator decides where tasks should run and when and places them in the available infrastructure most efficiently. You can think of the orchestrator as the conductor of a musical orchestra. Just as the conductor guides musicians, ensuring they play harmoniously and at the right tempo, a workload orchestrator coordinates tasks across the infrastructure.

Workload

In IT, a workload refers to the amount of work a computer system or application requires to complete a specific task and the resources it needs. For example, a web application that processes user requests and uses a database to store information is a type of workload. If multiple infrastructure resources are needed to run and scale the application, coordination is crucial for successful execution.

The most common types of workloads today are container-based, orchestrated by tools like Kubernetes, Mesos, or Docker Swarm. However, other workloads exist and are still in use, such as those not yet containerized for the cloud or applications that simply cannot or should not be containerized. Think, for instance, of some legacy applications or IoT devices.

Nomad

If you’ve been paying attention, you may have noticed that I’ve been talking about workload orchestration rather than container orchestration. That’s because not everyone runs their applications and processes using containers. Many organizations still run legacy applications, while others adopt cloud technologies, resulting in a mixed environment with one foot in the cloud and the other in a traditional data center.

Nomad takes a different approach to workload orchestration and scheduling, acknowledging that not all IT workloads are container-based. Nomad is a workload orchestrator that can handle traditional containers and non-containerized applications such as legacy apps, batch workloads, virtual machines, or binaries. You can think of Nomad as a workload-agnostic orchestrator that works with any workload in different environments.

Nomad Features

Nomad’s approach to workload orchestration has several unique features that distinguish it from other, more established orchestrators. Let’s explore some of these features:

Nomad Architecture

Nomad uses a client-server architecture, with the same binary running as a server or client, depending on the configuration file provided during launch. Servers utilize the Raft consensus protocol for leader election and a gossip protocol for inter-cluster communication.

Client-Server Architecture

Nomad’s architecture consists of servers and clients. Servers form a consensus group using the Raft protocol, which allows them to elect a cluster leader and maintain high availability. All servers work simultaneously to make scheduling decisions. Meanwhile, clients execute tasks according to the leader’s instructions.

Raft Consensus Protocol

The Raft consensus protocol requires 3 or 5 servers in a cluster to form a consensus group and elect a cluster leader. This configuration balances availability and performance. The leader processes queries and transactions while all servers contribute to scheduling decisions.

Reference Architectures

Now, look closely at Nomad’s deployment strategies and reference architectures.

Nomad cluster operates within a specific geographic region.

Best Practice for applications deployed in the same region.

Uses Consul for service discovery and dynamic configurations

Multi-Region

Federates multiple clusters (regions) to function as a single entity.

Enhances availability and scalability.

Regions can be within the same cloud provider, different providers, or private data centers.

Nomad and Kubernetes

When to Choose Nomad

Let’s consider scenarios where Nomad could be the better choice for your infrastructure needs:

• Mixed Workloads and Migration

Nomad is an excellent choice for organizations with a mix of traditional, cloud-native, and hybrid workloads. It can easily integrate existing workloads into the same cluster, simplifying migration strategies and enabling a unified platform.

• Performance and Scalability Needs

Nomad’s performance and scalability make it ideal for large-scale deployments with high performance and high availability requirements. Whether you operate a large data center, an IoT environment, or a cloud-native setup, Nomad can easily handle diverse workloads.

Conclusion

If you require a unified platform to handle diverse workloads or if you’re looking for a simple, scalable orchestrator, Nomad might be the perfect choice for your needs.

Drop a query if you have any questions regarding Nomad and we will get back to you quickly.

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