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10 posts tagged with "microservices"

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· 9 min read
Yulia Gavrilova

Microservice architecture is becoming more and more common in the realization of business ideas. Developers can easily add or remove features; update specific parts of applications without interfering with general workflow; and concurrently use diverse technologies and programming languages based on their business needs.

The microservice orchestrator controls the execution of processes in this distributed architecture and its role is increasingly important, as it makes it easier to uncover and fix problems, as well as manage the development of the entire system, even when we’re talking about systems that have more than one programming language in their tech stack.

In this article, you’ll learn about workflow orchestration and its benefits and limitations when building a microservice platform that features several programming languages.

· 5 min read
Doug Sillars

What is a workflow? Wikipedia says "A workflow consists of an orchestrated and repeatable pattern of activity, enabled by the systematic organization of resources into processes that transform materials, provide services, or process information."

None of that is incorrect. But it is certainly a mouthful. If I am asked in an elevator what a workflow orchestration is, I like to use analogies to make the point as approachable as possible:

"It's like a recipe for code. A recipe has a series of steps, that must be run in a specific order. Iyt can also have different options for food allergies, or different ingredients you might have on hand? A workflow is a recipe for your code, and can be built to handle many of the changes that might reasonably occur when the code runs."

Workflows as recipes

You may have seen one of the name videos out there of parents teaching kids code by writing out the steps to create a Peanut butter and Jelly sandwich.

We're not going to be quite as silly as that Dad, but we'll run through some instructions on how to create a PB&J from Instructables..

If you look at the URL of that recipe - it appears it took 4 tries to get it right :D https://www.instructables.com/How-to-Make-a-Peanut-Butter-and-Jelly-Sandwich-4/

The steps are (skipping some substeps for clarity):

  1. Gather Your Ingredients for the Sandwich
  2. Pull Out Two Slices of Bread
  3. Open Peanut Butter and Jelly
  4. Spread the Peanut Butter Onto One Slice of Bread
  5. Spread the Jelly Onto the Other Slice of Bread
  6. Combine the Two Slices
  7. Clean Up Your Workspace
  8. Enjoy Your Sandwich

(if you read closely, I skipped 3 steps - wearing gloves, removing the crust and cutting the sandwich in half... because, well - that's all just ridiculous)

The eight steps above are a workflow. They must be performed in that order to create a sandwich - you cannot spread the PB before you lay out the bread.

Building a Conductor Workflow

We can turn these 8 steps into a Conductor workflow.

PB&J example workflow

If you'd like to see the definition of this workflow, you can check out the code on the Orkes Playground. It's free to sign up.

This workflow shows clear steps with arrows pointing to the next step - so it is visually possible to see how the workflow will progress.

Improving the workflow

Each task is run by a microservice, so making changes and adding tasks is easy to do. In this example - you see that the recipe calls for PB to be spread first, and then the jelly. This works for a single human - these steps each take 2 hands. But there is no reason that the jelly cannot go first, and THEN the PB. Or - if you had more hands - the PB and the Jelly could be spread simultaneously.

Independent tasks

Let's remove the PB dependency from the jelly spreading - as the order of PB vs. jelly does not matter.

We can do this in Conductor with a FORK. A fork splits your workflow into 2 asynchronous tasks, and then a JOIN reconnects the the workflow into a single path.

We can now apply a fork to apply PB, and a second fork to apply the jelly:

PB&J example workflow

This is version 2 of the workflow, and you can see it in the playground

Now, these operations are independent, and if there is space in the jelly task queue - that can be completed ahead of the PB.

Recipe variations

Often, recipes have variations to preparation, and they can be read like an IF statement in programming (If (fresh tomatoes) {do x}, else if (tinned tomatoes) {do y}.

Cooking a burrito

Let's look at a common example - from a burrito in my freezer. The preparation directions vary depending on the cooking method.

burrito instructions

We can emulate this in a workflow using a switch task. The Switch task takes in the workflow ovenType input ${workflow.input.ovenType} and based on this value will make a decision. The default case is for the microwave, and then second decisionCase is set to "oven". From that input, the different tasks can be run.

burrito workflow

Conclusion

Workflows are a series of tasks that must be followed in a certain order. In this post, we used cooking recipes as an analogy to a workflow - they too are a series of tasks that must be followed in a certain order.

We created sample workflows for making a peanut and jelly sandwich (version 1 and version2) and another workflow to cook a frozen burrito with microwave or oven instructions.

<<<<<<< Local Changes We are able to reuse a number of tasks:

  • The zap task is used twice in the microwave branch.
  • The bake task in the oven branch.
  • The flip task is used in both branches.

When reusing tasks, the taskReferenceName (shown at the top of the box) must be unique.======= If you're curious about how to build a workflow orchestration - it might be a fun exercise to try your favorite recipe as a workflow. You can build on the workflows from this post in our free playground. Feel free to share what you came up with in our Discord. We love seeing creative uses of workflows!>>>>>>> External Changes

· 9 min read
Paul Ibeabuchi

Microservice architecture is an architecture where an application is split into separate services, and each service is run and managed independently. In a microservice architecture, every service is focused on handling one major function and is solely responsible for its own data management.

Microservice architecture is often recommended for larger applications because it allows services to be managed by dedicated teams. Testing and deployment also become easier, as they can be carried out independently for each service without affecting the overall application.

In this article, you'll learn what a microservice architecture is and when to use it, and about workflow orchestration, its benefits, and how it can be utilized in a microservice architecture. You'll also look at an example use case of microservice architecture so you can better understand the benefits, strengths, and weaknesses of this style of architecture.

· 14 min read
Nikhila Jain

A 2020 survey by the research and advisory firm Gartner has highlighted the rapid pace of innovation in cloud computing. According to the research, forty percent of enterprise solutions will host their applications on cloud infrastructure by 2023. This shifting trend will cause an increased demand for cloud services, as well as for hybrid cloud architecture.

The hybrid cloud is gaining popularity as enterprise IT leaders seek flexible, scalable options that increase cost efficiency while maintaining control over enterprise data and information. Many organizations combine on-premise infrastructure with private/public cloud resources to meet these needs.

But without the right strategy, hybrid clouds can pose a number of challenges. Through a hypothetical case study, this article will help you learn about the strengths and limitations of hybrid cloud architecture.

· 3 min read
Doug Sillars

Conductor is a workflow orchestration engine that connects all of your microservices together to create fully functional workflows that can run at scale. Each workflow is comprised of tasks - and many of these tasks are powered by external workers - or microservices. These workers can be written in any language - from Conductor's point of view - data goes in, and results come out - the language that processes the data is irrelevant.

Each worker has to connect to your Conductor instance, and regularly poll for work in the queue. There has long been Java, Go and Python SDKs to easily connect your apps to Conductor, but for building in other languages, this code had to be created by each development team.

Today, we announce that major improvements to the Golang and Python SDKs, and announce C# and Clojure SDKs.

Further, all of the (non-Java) SDKs have a new GitHub home: the Conductor SDK repository is your new source for Conductor SDKs:

Coming soon:

· 9 min read
Azeez Lukman

Microservices are a common and popular approach to building modular, scalable software with autonomous services. Large complex products are broken down into individual services responsible for a specific business function, such as user authentication or store checkout.

A microservice-based application might require several services to interact with each other to complete a business scope. The coordination of these interactions is known as a workflow or a saga. There are two models for implementing a workflow: choreography and orchestration. With choreography, you let each part of the system inform the other of its job and let it work out the details, while with orchestration, you rely on a central brain to guide and drive the execution processes.

As orchestrated systems have grown more expansive, the problem of efficiently orchestrating related business logics has become more pronounced. In this article, you will learn about the microservice orchestration workflow and its importance in relation to modern software architecture practices.

What is Microservice Orchestration?

A microservice orchestration pattern involves a central orchestration service (the orchestrator) that typically contains the entire business workflow logic and issues commands to and awaits responses from worker microservices. Think of this as an orchestra where a central conductor is responsible for keeping the orchestra in sync and coordinating the members to produce a cohesive musical piece. Using orchestrators for your application is essential for efficiently managing applications based on microservices.

Before going into the specifics of microservice orchestration, it is helpful to familiarize yourself with the components of microservice-based architecture. For example, in a microservice-based e-commerce application, the following could come into play during the process of purchasing a product:

  • a service for listing all products;

  • a service for adding products to the cart and reserving that product from the inventory;

  • a service for handling the payment; and

  • a service that manages the shipment of the item.

Each of these microservices is autonomous. In other words, microservices can be individually scaled up or down without having to worry about the entire application. However, they are all required to interact with each other to fulfill the purchase. It might be tempting to have the services talk to each other directly as needed. However, as your architecture and the number of services grow, this can quickly get messy and difficult to maintain. This is where orchestration comes into play.

A microservice orchestration workflow is an architectural method of coordinating microservices for software systems and applications, in which loosely coupled services receive commands from a central controller, referred to as the orchestrator. The orchestrator acts as a brain, driving the execution processes; it sends a call to each service and awaits a reply before proceeding. The concept of a microservice orchestration workflow can be best described through a hypothetical use case.

microservice orchestration workflow architecture diagram

The architectural diagram of this hypothetical use case shows the interactions between the various services involved in the process when following an orchestration workflow. Looking at the diagram above:

  1. The orchestrator receives a trigger that initializes the workflow, starting with “Products Service.”

  2. When this service has created an order with the products in the customer's cart, it returns some response to the orchestrator.

  3. The orchestrator then calls the “Inventory Service” to reserve the products in the cart.

  4. Next, the orchestrator calls the “Payment Service” to handle the payment.

  5. After successful payment, the orchestrator moves on to the “Shipping Service,” which clears the products for shipment.

In a choreography workflow, on the other hand, the microservices are not managed by a central service; however, they are all aware of the business goals and rely on certain events from other services that determine how they function. Each service publishes the actions it has taken to a message stream such as SQS or Kafka. Other services subscribe and listen for events they are interested in from these streams and take the appropriate actions.

choreography orchestration workflow architecture diagram

In the choreography architecture above:

  1. The “Products Service” creates an order with the items in the customer's cart and publishes an "Order Created" event to a stream on the messaging platform.

  2. The “Inventory Service” and “Payment Service” consume from this message stream. The “Inventory Service” handles reserving the products in the cart, and the “Payment Service” handles the payment and publishes the “Payment Success” event.

  3. On receipt of an inventory “Payment Success” event, the “Shipping Service” goes ahead and clears the products that were reserved for shipment to the customer.

Why is Microservice Orchestration Important?

Microservice architecture involves decomposing your application into a set of services to improve agility and allow teams to scale. One of the main purposes of this architectural pattern is to have each service as an independently deployable component with well-defined interfaces; in this way, the scope of implemented changes can be limited to a single service.

However, you must coordinate the execution of multiple microservices to deliver the outcomes that users want, and this is why microservice orchestration is important. Orchestration allows you to put a service in charge of the other services. The service in charge is aware of the entire flow that is required and is responsible for putting the other services to work to achieve those aims.

Microservice orchestration enables you to process flows ranging from simple linear workflows to very complex dynamic workflows that run for multiple days with minimal effort and high visibility into the processes. To properly illustrate the benefits you can obtain with an orchestration workflow when managing your microservices, let’s take a look at a case study from Netflix.

Netflix is an enterprise company that has shifted toward orchestration workflows. The streaming service had traditionally used the choreography method, which involves peer-to-peer tasks that are tightly coupled; this became harder to scale with growing business needs and associated increasing complexities like determining what remains for a movie setup to be complete and updating their SLAs.

Later, Netflix switched to an orchestration workflow and eventually built their own container orchestration engine—Conductor—which has helped orchestrate over 2.6 million process flows, from simple linear workflows to complex dynamic workflows over multiple days.

Why Are So Many Developers Adopting This Architectural Paradigm?

As mentioned, there are two major techniques you can use if you need to execute many services to get your desired result. Orchestration, in which a central orchestrator component serves as the coordinator and is in charge of activating each service, and choreography, in which the services perform independently and are only loosely connected.

Developers are increasingly adopting orchestration because it has significant benefits that can make development and management easier for individual microservices without compromising the big picture. However, it should be noted that microservice orchestration is not without its limitations.

Benefits and Limitations of Microservice Orchestration

There are several benefits and challenges associated with the implementation of an orchestration workflow, many of which are related to how microservices interact with one another to achieve a business outcome.

Benefits of Microservice Orchestration

Central observability of process definition, status, and metrics: The orchestration framework can capture detailed information about each executed process instance, which it can make available for analytics. This allows you to answer questions about specific instances (such as, “Where is my order?”), as well as analytical queries (such as, how many products were ordered).

Synchronous processes: These provide a good way to control the process flow. For example, when a product’s service needs to successfully complete before the inventory service is processed.

Scalable orchestration on cloud-native platforms: When you scale up these services, you scale with errors in mind. Microservice orchestration provides you with insights into your processes, helping you coordinate various transactions that involve a large number of independent services.

Single fail point: Orchestration workflow allows you to easily trace out any error that occurs during the process flow, figure out why it failed, and debug. Writing tests for your microservices is important to help prevent errors from making it to the live service.

Limitations of Microservice Orchestration

When orchestrating microservices in an enterprise environment, you’ll find that some business functions can require hundreds or even thousands of microservices. Since the orchestration workflow is synchronous, it's possible that such processes will take a long time to finish.

Furthermore, as the orchestrator needs to communicate with each service and get a response before moving to the next, this makes services highly dependent upon each other. Failure at any point could cause the entire process to fail. While for some business processes this is required behavior, others might require the process to complete regardless; for instance, running analytics on an order that’s being processed shouldn’t prevent the checkout flow from being completed.

Who Can Benefit from Microservice Orchestration?

With microservices gradually becoming the default pattern for managing business logics, a strong architecture is needed for their coordination. Adopting an orchestration workflow could improve the seamless interaction between these services.

Many businesses still implement service-oriented architectures (SOAs) orchestrated by an enterprise service bus (ESB). However, as business needs grow, adding more business logics and microservices to the system can be challenging; the entire flow is not immediately visible, making it harder to alter a service without the risk of disrupting another.

Microservice orchestration offers a solution here, as it helps you visualize the end-to-end processes across your microservices, so you know what services would be affected by your updates, allowing you to easily address your increasing business needs.

More concretely, an orchestration workflow might be ideal for you if one or more of the following are critical for your business:

  • The ability to track and manage workflows from a single point.

  • A user interface to visualize process flows.

  • The ability to synchronously process all tasks.

  • The ability to efficiently scale to a high number of concurrently running process flows.

  • A queuing service abstracted from clients.

  • The requirement to operate services over HTTP or other transport layers such as gRPC.

Conclusion

In this article, you learned about the importance of keeping your microservices autonomous and flexible. You also learned about the use of microservice orchestration to effectively communicate, visualize, identify, and resolve the challenges of managing microservices.

The downside of the process of building an orchestration system that implements all of the features your business requires is that it’s rather complex and time consuming. A purpose-built framework offering scalable and low-overhead orchestration— like Netflix’s Conductor, is an open source tool that fits this purpose.

Orkes is a platform that offers a fully managed, cloud-hosted version of Conductor with tiered support. Orkes builds on top of Netflix Conductor to abstract out installation, tuning, patching, and managing high-performing Conductor clusters. Learn more about Orkes and get started for free within minutes here.

· 2 min read
orkes

What is Conductor

Conductor is a Microservices orchestration platform from Netflix, released under Apache 2.0 Open Source License.

Design for failures

Failures and service degradation are the fact of any system, this is especially true with large interconnected systems running in cloud. Conductor is designed with principles that systems can and will go down, degrade in performance and any dependencies should be able to handle such failures.

Tasks in Conductor

Conductor workflows are orchestration of many activities known as task. Each task represents a (ideally) stateless worker that given a specific input does the work and produces output. The tasks are typically running outside of Conductor server and there are many factors that could effect their availability.

Designing for failures

Conductor allows you to define your stateful applications that can handle failures and temporary degradation of services and without having to write code for that.

Configuring tasks to handle failures

Each task in Conductor can be configured how it responds to availability events such as: 1) Failures 2) Timeouts and 3) Rate limits.

Here is a sample task definition:

{
"createdBy": "user",
"name": "sample_task_name_1",
"description": "This is a sample task for demo",
"responseTimeoutSeconds": 10,
"timeoutSeconds": 30,
"timeoutPolicy": "TIME_OUT_WF",
"retryCount": 3,
"retryLogic": "FIXED",
"retryDelaySeconds": 5,
"rateLimitPerFrequency": 0,
"rateLimitFrequencyInSeconds": 1
}

retry* parameters specify how to handle cases where the task execution fails and retries can be configured to be with fixed delay or exponential backoff. Similarly timeout* parameters specify how much time to give for task to complete execution and if the task should be marked as 'Timed Out' if it runs longer than that.

More Details

https://orkes.io/content/docs/how-tos/Tasks/task-configurations

Follow us on https://github.com/Netflix/conductor/ for the source code and updates.

· 6 min read

Microservices have emerged as the dominant application development paradigm in the software world today. It has tremendous benefits both from a business and technical perspective due to its fundamental characteristics of agility, scalability, and resiliency.

However, implementing microservices are hard! The inherently distributed nature of this architectural pattern introduces complexity across multiple areas especially around Transaction Management, Data Consistency, and Process Automation. In a distributed system, Business Transactions can span across multiple services. Since we no longer have the ability to run a single ACID transaction, it requires careful coordination across these services to ensure that you have a consistent and reliable system at the end of a business process.

Solutions to solve this “coordination” problem have led to the rise of a new set of application patterns that can be broadly classified into two main groups - Choreography and Orchestration.