[Microservices] Create and Deploy Microservices

IBM Cloud Code Engine

Challenges of self-hosting microservices

Deliberated Configuration and Build

Manage Infrastructure

Dynamic Scaling

Communication and Security

Logging and Monitoring

Example: Deploy a Python-based microservice

IBM Cloud Code Engine

Just push the code to the cloud and done:

• Description: IBM Cloud Code Engine abstracts the operational burden of building, deploying, and managing workloads, allowing developers to focus solely on code development.
• Key Features:
  • Fully managed serverless platform.
  • Developers can push code without worrying about underlying infrastructure.
  • Runs workloads such as microservices, web apps, event-driven functions, or batch jobs seamlessly.

Main use cases:

1. Deploy application:
   • Developers can deploy built applications to Code Engine, representing microservices, web apps, or console apps.
2. Build and deploy:
   • Code Engine can build applications directly from source code, either from a remote repository or local workspace, and automatically deploy them.
3. Run jobs:
   • Create and run batch jobs, such as data processing or analytics tasks, on Code Engine alongside deployed microservices.

Main Benefits:

• Focus on your code:
  • Developers can focus entirely on writing code without worrying about cluster management or infrastructure.
• Go live in seconds:
  • Build and deploy apps in seconds, facilitating rapid deployment of emergent updates.
• Auto-scale:
  • Code Engine automatically scales workloads up and down based on demand.
• Control access:
  • Platform and services access permissions are controlled based on IBM Cloud infrastructure and access management.
• Secure private network:
  • Provides secure connections using Transport Layer Security (TLS) and isolates workloads within the IBM Cloud infrastructure.
• Integrates with other IBM Cloud Services:
  • Fully integrates into the IBM Cloud ecosystem, enabling seamless utilization of other IBM Cloud services from within Code Engine.
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Project, Application, Build and Job

Project:

Description: In IBM Cloud Code Engine, a project serves as a logical grouping mechanism for managing resources and entities such as applications, builds, jobs, and certificates for Transport Layer Security (TLS) HTTPs connections. It provides a centralized workspace for organizing and coordinating related entities within a Code Engine environment.

Key Features:

1. Resource Management: Projects enable efficient organization and management of resources within Code Engine. By grouping related entities together, projects help streamline resource allocation, monitoring, and access control.

2. Namespace Provisioning: Each project in Code Engine provides a namespace for its associated entities. A namespace acts as a unique identifier that isolates groups of entities and resources within a single project. Names of entities must be unique within a namespace, ensuring namespace-level integrity.

3. Access Control: Projects facilitate access control by defining permissions and policies for managing resources within the project. Administrators can configure fine-grained access controls to regulate user access, resource provisioning, and operations within the project.

4. Auditing and Monitoring: Projects support auditing and monitoring of resource usage and activities. Administrators can track changes to resources, monitor resource allocation, and analyze resource consumption trends to optimize resource utilization and performance.

5. Resource Summary: Projects provide a summary view of all associated entities, including applications, builds, jobs, and certificates. This summary enables users to quickly assess the status and availability of resources within the project.

6. Resource Allocation: Projects enable monitoring of resource allocation and utilization for the entire project. Metrics such as total CPU usage, memory consumption, and storage utilization help administrators optimize resource allocation and ensure efficient resource utilization.

Use Cases:

• Multi-Tenant Environments: Projects are particularly useful in multi-tenant environments where multiple users or teams share a Code Engine instance. Each tenant can have its own project, providing a segregated workspace for managing resources and applications independently.

• Resource Isolation: Projects facilitate resource isolation by providing dedicated namespaces for each project. This isolation ensures that entities within a project operate independently and do not interfere with resources in other projects.

• Access Control: Projects support access control policies that allow administrators to enforce security measures and regulate user access to resources within the project. This helps prevent unauthorized access and ensures compliance with security standards and regulations.

• Resource Management: Projects simplify resource management by providing a centralized workspace for organizing and coordinating related entities. Administrators can easily monitor resource usage, track changes, and optimize resource allocation within the project.

Benefits:

• Organization: Projects provide a structured and organized framework for managing resources and entities within Code Engine. This helps streamline resource management and enhances overall operational efficiency.

• Isolation: Projects facilitate resource isolation and namespace provisioning, ensuring that entities within a project operate independently and do not impact resources in other projects.

• Access Control: Projects support fine-grained access control policies, allowing administrators to regulate user access and permissions within the project. This helps enforce security measures and mitigate risks associated with unauthorized access.

• Monitoring and Optimization: Projects enable monitoring and optimization of resource allocation and utilization, helping administrators optimize performance, identify bottlenecks, and improve resource efficiency.

Overall, projects serve as a foundational building block for managing resources and entities within IBM Cloud Code Engine. By providing a centralized workspace, resource isolation, access control, and monitoring capabilities, projects help streamline resource management and enhance operational efficiency in Code Engine environments.

Application:

• Description: In IBM Cloud Code Engine, an application represents a deployable unit of code that serves a specific purpose, such as running a web service, processing data, or executing business logic. Applications encapsulate one or more containerized services or microservices and are designed to handle incoming HTTP requests or create WebSocket sessions.

  Key Features:

  1. Code Execution: Applications run executable code to serve HTTP requests or create WebSocket sessions. They act as the primary interface for interacting with end-users or external systems.

  2. Service Composition: Applications may comprise multiple containerized services or microservices that work together to fulfill a common functionality or business requirement. Each service within the application performs a specific task or handles a subset of requests.

  3. HTTP and WebSocket Support: Applications support both traditional HTTP requests and WebSocket communication protocols. This enables developers to build interactive web applications, real-time messaging systems, and other types of networked services.

  4. Scalability: Code Engine automatically scales applications based on incoming workload and configuration settings. It dynamically adjusts the number of running instances to handle fluctuations in traffic and ensure optimal performance.

  5. Configuration Management: Applications can be configured with various settings, such as resource limits, environment variables, networking parameters, and deployment strategies. These configurations allow developers to tailor the behavior and performance of the application to meet specific requirements.

  6. Deployment Options: Applications can be deployed to Code Engine from either a registered container image or directly from the source code. This flexibility allows developers to choose the deployment method that best fits their workflow and development practices.

  Use Cases:

  • Web Services: Applications are commonly used to deploy web services, APIs, and backend systems that handle HTTP requests from client applications or users. They serve as the entry point for interacting with the underlying business logic or data processing pipelines.

  • Real-Time Communication: Applications support WebSocket communication, making them suitable for building real-time messaging systems, chat applications, multiplayer games, and other interactive applications that require bidirectional communication between clients and servers.

  • Microservices Architecture: Applications are often designed following a microservices architecture, where each microservice encapsulates a specific business function or domain. This modular approach allows for better scalability, maintainability, and flexibility in large-scale applications.

  • Data Processing: Applications can be used to deploy data processing pipelines, batch jobs, or stream processing systems that ingest, transform, and analyze large volumes of data. They provide a scalable and efficient platform for executing data-intensive workloads in the cloud.

  Benefits:

  • Modularity: Applications enable developers to modularize their codebase into discrete units of functionality, making it easier to manage and maintain complex systems.

  • Scalability: Code Engine automatically scales applications up or down based on incoming workload, ensuring optimal performance and resource utilization.

  • Flexibility: Applications support various deployment options, configuration settings, and communication protocols, allowing developers to customize the behavior and performance of their applications according to specific requirements.

  • Ease of Deployment: Applications can be deployed to Code Engine with minimal effort, either from a container image or directly from the source code. This streamlined deployment process accelerates time-to-market and facilitates rapid iteration and experimentation.

  Overall, applications play a crucial role in IBM Cloud Code Engine by providing a scalable and flexible platform for deploying, managing, and scaling containerized services and microservices. They serve as the backbone of modern cloud-native applications, enabling developers to build and deploy a wide range of web services, data processing pipelines, and real-time communication systems in the cloud.

Build:

• A build in IBM Cloud Code Engine is the process of creating a container image from your source code. It's a critical step in deploying applications to Code Engine, as container images contain all the assets necessary for a container to run, including executable source code, dependencies, system libraries, configuration settings, and resources.

  Key Features of a Build:

  1. Container Image Creation: The primary function of a build is to generate a container image that encapsulates your application code and its dependencies. This image serves as the runtime environment for your application when deployed to Code Engine.

  2. Source Code Transformation: During the build process, Code Engine transforms your source code into a format that can be executed within a containerized environment. This may involve compiling code, resolving dependencies, and preparing the application for deployment.

  3. Dockerfile or Buildpacks: Code Engine supports two main methods for building container images: using a Dockerfile or Cloud Native Buildpacks. A Dockerfile is a text file that contains instructions for building a Docker container image, while Buildpacks are a set of scripts and utilities that automate the build process by analyzing source code and assembling a container image based on detected dependencies.

  4. Dependency Resolution: Builds automatically resolve dependencies required by your application, ensuring that the resulting container image contains all the necessary components to run your code without additional configuration.

  5. Customization: You can customize the build process by specifying parameters such as build context, build cache settings, and build environment variables. This allows you to tailor the build process to meet the specific requirements of your application.

  6. Automatic Deployment: Once the container image is successfully built, it can be automatically deployed to Code Engine as an application. This seamless integration streamlines the deployment process, eliminating the need for manual intervention.

  Use Cases for Builds:

  • Continuous Integration/Continuous Deployment (CI/CD): Builds are commonly used in CI/CD pipelines to automate the process of building, testing, and deploying applications. By integrating builds into CI/CD workflows, developers can ensure that changes to the codebase are automatically built into container images and deployed to production environments.

  • Application Packaging: Builds are essential for packaging applications into portable and reproducible container images. This allows developers to deploy applications consistently across different environments, such as development, staging, and production, without encountering compatibility issues.

  • Version Control: Builds help enforce version control best practices by generating unique container images for each version of the application. This enables developers to track changes to the codebase over time and roll back to previous versions if necessary.

  Overall, builds play a crucial role in the software development lifecycle by facilitating the transformation of source code into deployable container images. By automating the build process and providing support for various customization options, Code Engine simplifies the task of creating and managing containerized applications in the cloud.

Job:

• Description: A job in IBM Cloud Code Engine represents a one-time execution of code. It is designed for tasks that need to be performed periodically or as a one-off operation, rather than continuously serving incoming requests like applications. Jobs are particularly useful for executing tasks such as data processing, machine learning model training, reporting, and billing.

  Key Features:

  1. One-time Execution: Unlike applications, which may run continuously to handle incoming requests, jobs run once and then exit after completing their task. This makes them suitable for tasks that do not require continuous execution.

  2. Workload Configurations: Before running a job in Code Engine, you can specify workload configurations that dictate how the job should run. These configurations include parameters such as resource limits, environment variables, and execution constraints.

  3. Instance Creation: Depending on the workload and configuration settings, Code Engine may create one or more instances of a job to execute concurrently. Each instance runs the same executable code to perform the specified task.

  4. Task Types: Jobs can be used for a variety of tasks, including:

     • Data processing jobs: Querying and transforming data in batches.
     • Machine learning model training jobs: Training machine learning models on data.
     • Reporting jobs: Generating reports based on preset schedules or triggers.
     • Billing jobs: Creating and sending bills or invoices to customers.

  Use Cases: Jobs are suitable for scenarios where tasks need to be executed periodically, on-demand, or as part of a specific workflow. Some common use cases include:

  • Performing periodic data processing tasks, such as aggregating data from multiple sources or cleaning and transforming datasets.
  • Training machine learning models on new data periodically or in response to specific triggers, such as the availability of new training data.
  • Generating reports or analytics based on predefined schedules or business events, such as daily, weekly, or monthly summaries.
  • Automating billing or invoicing processes by generating bills or invoices based on usage data or subscription plans.

  Benefits:

  • Efficiency: Jobs enable efficient execution of one-time or periodic tasks without the need for continuous infrastructure provisioning or management.
  • Scalability: Code Engine can scale jobs dynamically based on workload demands, allowing for efficient resource utilization and faster task completion.
  • Automation: Jobs can be scheduled to run automatically based on predefined schedules, triggers, or events, reducing the need for manual intervention.
  • Resource Isolation: Each job instance runs in isolation from other instances, ensuring that tasks are performed independently and securely without interference from other workloads.