Application orchestration refers to the automation of workflows that coordinate and manage communications and requests between application services and/or databases.
Cloud native applications typically rely on containers and microservices as part of their architecture, which comes with the burden of managing calls between services. This cloud architecture approach, while manually manageable, achieves better system efficiencies if automated.
Automation differs from orchestration in its scope. Automations are designed to be single tasks that are easily and quickly completed by machine. Whereas, orchestrations are workflow automations made up of these building block automations. In this, automation and orchestration are closely related but different concepts.
Application orchestration overlaps container orchestration, and is often used interchangeably. To clarify, orchestration in the sense of corralling automations workflows together is used in many computing domains, including “container orchestration”. Container orchestration is the practice and processes of organizing containers and allocating resources to them at scale. This differs from containerization software, such as Docker, which creates and acts as a container’s runtime. Container orchestration software typically coordinates several virtual and physical machines each with their own containerization software installed.
There are several vendor application orchestration platforms, each with their specific algorithm for orchestrating data. For a basic working model, the following is a brief description of Oracle’s Communication Service Broker, which performed application orchestration.
For Oracle, “orchestration is the ability of Service Broker (SB) to route a session through various applications.” This means that the SB acts as traffic controller, routing sessions sequentially from one application execution to the next until the session control is passed back to the network entity. This works in three stages:
The session is received by the Orchestration Engine (OE) through a network module.
Orchestration Logic, set out by the developers, routes the session through the pre-defined sequential applications, moving onto the next application as the last one is completed.
After passing all the applications, the OE passes the session control back to the network entity.
Application orchestration requires integration. Depending on the application, perhaps deep integrations. It is always advisable, when working with vendor platforms, to consult a product specialist to determine if it will meet current and future needs.
Automations chained together in orchestrated workflows provide several benefits, mostly all, though, improve the efficiency of operations.
Time and Cost Savings — Assigning mundane tasks to machines reduces the time it takes to perform those tasks. The time savings translates into multiple benefits, least of which is cost savings. By reclaiming valuable human time, which is always slower at mundane tasks than machines, those hours can be reallocated to solving complex problems, like cyber security threats, where machines can’t apply creative thinking.
Decreased Human Errors — Machine communication immediately decreases human error. While automations can produce errors, these results can often be traced back to bugs, or other errors introduced by a human developer. However, when automations run well, they make scaling applications and systems possible.
Improved Overall Experience — This is applicable for both end users and developers. Developers can build more resilient and efficient systems, while users benefit by seeing incremental performance improvements.
Increased Productivity — Directly tied to time savings, by eliminating many hours spent developing, debugging, and fixing software problems, developers can turn their attention to other important matters.
Standardized Workflows — Automations and orchestrations define standard workflows that help bring up efficiency, and provide a base as the company grows to build out services.
Netflix deploys multiple containers using its open source container orchestration systems called Titus. Netflix uses a lot of containers, launching as many as 3 million every week. Managing all of the services within these containers, let alone the communication between them, is simply mind-bogglingly impossible without automation and orchestration software.
Container, or application, orchestration platforms can be found for every major cloud provider. However, many of them are based on the popular open-source container orchestration software Kubernetes. The following are some of the most familiar names in container cloud services.
Amazon Elastic Container Service (Amazon ECS) — Amazon ECS is their home-grown version that runs and manages Docker containers. It's a fully managed service which integrates very well into the Amazon suite of services, while essentially offering consumers a serverless experience.
Amazon Elastic Kubernetes Service (Amazon EKS) — Amazon EKS is Amazon's Kubernetes solution, which is also a managed platform for Kubernetes in an AWS services subscription. This setup allows for hybrid and multicloud environments, whereas ECS does not.
Kubernetes — The de facto container orchestration software, and it’s open source.
Mirantis Kubernetes Engine (formerly Docker Enterprise) — Docker enterprise is a set of advanced enterprise development features that works with Docker and Kubernetes to provide a shared platform across dev and ops in the context of deploying to containers. For developers, and enterprises, this is the industry leading DevOps platform for building and running modern containerized applications.
Google Kubernetes Engine (GKE) — Google promotes their powerful cloud technology running a Kubernetes engine.
Red Hat OpenShift Container Platform — An open source, out-of-the-box container orchestration solution for Linux.
Kubernetes is open-source, and largely considered the gold standard for container orchestration, though, as stated above, and because it is highly portable, there are many vendors to choose from that can accommodate it. Kubernetes is highly flexible and used in the delivery of complex applications. Docker container orchestration, or Docker Swarm, is Docker’s flavor of orchestration software that is included with Docker. Both are solid and effective solutions for massively scaling deployments, as well as implementation and management.
● Kubernetes focus on high demand use cases with complex configurations,
● Docker Swarm prompts ease of use and simple and quick deployed use cases
The following table highlights several comparisons between the two.
App Definition & Deployment
Desired state definition in YAML file
Desired State definition
No autoscaling possible
Cluster autoscaling, horizontal pod autoscaling
Service replication at Swarm Node level
Stacked Control Plane node with load balancing either inside or outside the cluster
AWS, Azure, Google
Graphic User Interface (GUI)
GUI not available; must use 3rd party tools
GUI is available; web interface
No auto load balancing, but port exposure for external load balance services
Horizontal scaling & load balancing
Logging and Monitoring Tool
No monitoring out-of-box, use 3rd party integrations
Built-in tool for logging and monitoring, 3rd party integrations
Multi-layered overlay network with peer-to-peer distribution among hosts
Flat peer-to-peer connections between pods and nodes
Storage Volume Sharing
Shares storage with other container
Shares storage within the same Pod
Updates & Rollbacks
Rolling updates and service health monitoring
Automated rollouts & rollbacks
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