An Introduction To DevOps Processes and Their Significance

In traditional software development methodologies, the time taken for code deployment was a major setback. One of the main reasons for slower code deployment was the lack of consistency between the development and the operations teams. To bridge this gap, the concept of DevOps came into action.

DevOps solutions and services provide continuous monitoring and integration of the tasks being performed by development and operations teams. It brings developers and operations experts under the same roof to improve the efficiency of IT processes. DevOps is increasingly becoming popular amongst IT companies because it helps them effectively meet the dynamic requirements of the IT infrastructure.

Also read Tips For Improving The Efficiency of DevOps Processes

What Is DevOps?

DevOps is a software development strategy that bridges the gap between the development and operations teams. It is a set of practices that works to automate and integrate the processes between software development and IT infrastructure management. As a result, it streamlines the entire workflow so they can build, test, and release software faster and more reliably.
 

How It works?

DevOps is a philosophy that involves both development and operations teams to work together throughout the project development lifecycle. From product design to its release and support, DevOps ensures accelerated processes with a focus on continuous delivery and continuous integration. It unites several effective tools like Agile, Git, Gradle, Jenkins, and more to accelerate the software development lifecycle and reduce time-to-market. 

Let’s discuss DevOps processes and explore the DevOps roadmap in detail through the following stages:

Planning

This is the first stage where the DevOps teams discuss the project goals and requirements with their clients and formulate an execution strategy.

Coding

Once the plan is finalized, the programmers can design and code the application. With tools like Git, developers have a repository to store all the codes and their different versions. It helps them work on the same codebase rather than working on bits of code for different operations.

Build

In this stage, the codes from different repositories are combined to build the complete application. Tools like Maven and Gradle enable developers to execute this process.

Testing

Before its deployment, the application is tested using automation tools like Selenium and JUnit to detect and fix bugs that are essential to ensure software quality.

Integration

It is the core of the DevOps working cycle that makes this methodology so effective. Tools such as Jenkins enable developers in the process of sending the codes for building and testing. When the testing is complete, it is further sent for deployment. This process is called continuous integration.

Deployment

In this stage, the application is packaged after release and deployed from the development server to the production server.

Operation

Once it is successfully deployed, the operations team configures the servers, provisioning them with the required resources. Tools such as Chef, Docker, and Ansible are effective at operating and managing various productions.

Monitoring

Every product is continuously monitored in its own working environment. Continuous monitoring enables IT companies to identify specific issues with various releases. It helps them understand the impact of their product on end-users, thus providing the best possible solution for each client.

Benefits

Collaboration and Trust

It is one of the most important elements of the DevOps culture as it brings both development and operation teams to work in collaboration. In doing so, they can establish a culture of shared responsibility, transparency, and faster feedback.

Improved Defect Detection

The development team designs and develops each block of functionality of an application. Then the application is immediately tested and taken over by the operations team for finalizing the deployment process. Working cohesively makes it easier to detect any loopholes that may arise in the process and to increase the stability of the platform.
 

Accelerate Time to Resolution

DevOps teams are equipped with fully transparent and seamless modes of communication. As a result, they are able to resolve critical issues in less time without any frustration between the development and operations teams. DevOps teams can discuss the issues freely, fix the bugs, and solve the matters faster and more efficiently.
 

Increased Effectiveness

DevOps offers a combination of several tools and effective practices that enables IT companies to automate testing, deployments, and provisioning of services. It lets them reduce repetitive tasks and allows them to focus on their core operations. At the same time, it ensures higher productivity at work and aids in delivering higher quality outputs.

You may also be interested in reading The Significance of DevOps For Technology Companies

Conclusion

DevOps is an approach to development that revolves around the concept of collaboration. Its main idea is simply the cohesive working of the development and operations teams for enhancing the quality of end-products. It is an evolution of the agile methodology. In addition, DevOps services enrich the development process through continuous configuration, delivery, monitoring, and continuous integration.
 

Why Choose Oodles Technologies For DevOps Consulting Services?

We are an accomplished software development company that specializes in providing DevOps solutions and services to accelerate and improve the software development lifecycle. Our experienced team of developers and operations experts work together to meet the client’s requirements through DevOps. Our DevOps professionals are skilled at using various tools and practices to produce optimum results.

An Introduction To Kafka Architecture and Kafka as a Service

Kafka and Kafka as a Service

Apache Kafka is a fast and scalable Publish/Subscribe messaging platform. It enables the communication between producers and consumers using messaging-based topics. It allows producers to write records into Kafka that can be read by one or more consumers per consumer group. It's becoming a solution for big data and microservices applications. It is being used by several companies to solve the problem of real-time processing. AWS development services also render support for Apache Kafka via its fully managed Amazon MSK (Amazon Managed Streaming for Kafka) platform.

A Broker is like a Kafka server that runs in a Kafka Cluster. Kafka Brokers form a cluster. The Kafka Cluster consists of many Kafka Brokers on several servers. Brokers often refer to more of a logical system or as Kafka as a whole.

It uses ZooKeeper to manage the cluster. ZooKeeper is used to coordinate the brokers/cluster topology. ZooKeeper gets used for leadership elections for Broker Topic Partition Leaders.

The Kafka architecture consists of four main APIs on which Kafka runs.

1. Producer API:

This API allows an application to publish a stream of records to one or more Kafka topics.

Consumer API

It allows an application to subscribe to one or more topics. It also allows the application to process the stream of records that are published to the topic(s).

Streams API

This streams API allows an application to act as a stream processor. The application consumes an input stream from one or more topics and produces an output stream to one or more output topics thereby transforming input streams to output streams.

Connector API

This connector API builds reusable producers and consumers that connect Kafka topics to applications and data systems.

Kafka Cluster Architecture

Kafka architecture can also be described as a cluster with different components. 

Kafka Broker

A Kafka cluster often consists of many brokers. One Kafka broker can be used to handle thousands of reads and writes per second. However, since brokers are stateless they use Zookeeper to maintain the cluster state.

Kafka ZooKeeper

This uses ZooKeeper to manage and coordinate Kafka brokers in the cluster. The ZooKeeper notifies the producers and consumers when a new broker enters the Kafka cluster or if a broker fails in the cluster. On being informed about the failure of a broker, the producer and consumer decide how to act and start coordinating with other active brokers. 

Kafka Producers

This component in the Kafka cluster architecture pushes the data to brokers. It sends messages to the broker at a speed that the broker can handle. Therefore, it doesn’t wait for acknowledgments from the broker. It can also search for and send messages to new brokers exactly when they start.

Kafka Consumers

Since brokers are stateless, Kafka consumers maintain the number of messages that have been consumed already and this can be achieved using the partition offset. The consumer remembers each message offset which is an assurance that it has consumed all the messages before it. 

Kafka cluster setup via Docker

version: '2'

services:

  zookeeper:

    image: wurstmeister/zookeeper

    ports:

      - "2181:2181"

  kafka-1:

    image: wurstmeister/kafka

    ports:

      - "9095:9092"

    environment:

      KAFKA_ADVERTISED_HOST_NAME: kafka1

      KAFKA_ADVERTISED_PORT: 9095

      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181

      KAFKA_LOG_DIRS: /kafka/logs

      KAFKA_BROKER_ID: 500

      KAFKA_offsets_topic_replication_factor: 3

    volumes:

      - /var/run/docker.sock:/var/run/docker.sock

      - kafka_data/500:/kafka


  kafka-2:

    image: wurstmeister/kafka

    ports:

      - "9096:9092"

    environment:

      KAFKA_ADVERTISED_HOST_NAME: kafka2

      KAFKA_ADVERTISED_PORT: 9096

      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181

      KAFKA_LOG_DIRS: /kafka/logs

      KAFKA_BROKER_ID: 501

      KAFKA_offsets_topic_replication_factor: 3

    volumes:

      - /var/run/docker.sock:/var/run/docker.sock

      - kafka_data/501:/kafka


  kafka-3:

    image: wurstmeister/kafka

    ports:

      - "9097:9092"

    environment:

      KAFKA_ADVERTISED_HOST_NAME: kafka3

      KAFKA_ADVERTISED_PORT: 9097

      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181

      KAFKA_LOG_DIRS: /kafka/logs

      KAFKA_BROKER_ID: 502

      KAFKA_offsets_topic_replication_factor: 3

    volumes:

      - /var/run/docker.sock:/var/run/docker.sock

      - kafka_data/502:/kafka

Start The Cluster

Simply start the cluster using the docker-compose command from the current directory:

$ docker-compose up -d

We can quickly check which nodes are part of the cluster by running a command against zookeeper:

$ docker-compose exec zookeeper ./bin/zkCli.sh ls /brokers/ids

And that’s it. We’ve now configured a kafka cluster up and running. We can also test failover cases or other settings by simply bringing one kafka node down and seeing how the clients react.

Self-managed Kafka Services

We can also use Cloud-based self-managed kafka service on different cloud providers. cloud software development services provide fully managed and secure Apache Kafka service like Amazon MSK (Amazon Managed Streaming for Apache Kafka).

An Introduction To Amazon Managed Streaming For Apache Kafka

The popular video stream-processing software, Apache Kafka has gained significant traction over the recent years. The open-source tool that is mainly used for processing live streaming data, Kafka provides real-time analytics to derive maximum value from the streaming media content. Kafka has grown tremendously as many organizations have adopted this platform for building real-time data pipelines and video streaming applications. That being said, over one third of the fortune 500 companies use Kafka to run and manage their video streaming operations.

Seeing its increasing popularity, Amazon rendered its cloud support for Kafka to build and deploy applications that facilitate video stream processing. With the advent of Amazon MSK (Amazon Managed Streaming for Kafka), it has become easy to build and run real-time data pipelines and streaming applications. Amazon MSK also lets you populate various data lakes and stream variations from databases. Furthermore, you can use it to power machine learning algorithms and build applications with real-time analytics features.  

Also read How Startups Can Benefit From AWS IoT Core

Challenges With Apache Kafka

Despite the many benefits, Apache Kafka clusters are not easy to set up, scale, and manage in the production environment. Developers must manually configure Kafka before they can run it. Additionally, it requires provision servers, in case your existing servers incur any unanticipated failure. 

Developers must orchestrate server patches, system upgrades, optimize clusters, and consistently manage scaling events to support load changes. Above all, developers need to ensure that data is securely stored for easy accessibility.  

How Amazon MSK Overcomes These Challenges

Amazon Managed Streaming for Kafka (MSK) enables developers to build and run streaming applications on Apache Kafka with ease. With Amazon MSK, they do not require expertise from Kafka infrastructure management services as Amazon renders complete support for building and deploying applications. As a result, developers can focus on the core development operations without getting into complexities of infrastructure management. 

How It Works?

Amazon MSK console lets you create fully managed Apache Kafka clusters that are easy to configure, run, and deploy. With MSK, you do not need to acquire provisional servers as it automatically runs Kafka clusters on the AWS cloud. 

In addition, Amazon MSK continuously monitors cluster performance and replaces faulty nodes with new ones to ensure smooth app functioning. It also provides top-notch security to Kafka clusters by enabling end-to-end data encryption. 

Benefits of Amazon MSK

Amazon MSK provides a fully managed, secure, and more efficient way to run, manage and deploy Apache Kafka clusters. Below are the main enterprise benefits of using Amazon Managed Streaming for Apache Kafka. 

Fully Managed

Amazon MSK enables developers to build scalable streaming applications with Kafka without using Apache Kafka infrastructure. It also eliminates the requirement of procuring provisional servers as the clusters can be managed directly on the AWS cloud. In addition, it significantly reduces the complexities related to configuration and maintenance of Kafka clusters and Apache ZooKeeper nodes. 

Compatibility

Amazon MSK renders open-source compatibility and provides full support for third-party tools like Apache Flink, Spark, and HBase. It is also fully compatible with tools like Flume, Storm, Prometheus, and MirrorMaker.

Security

It provides multi-fold security for Kafka clusters at different levels of operations. The top-tier security rendered by Amazon MSK includes VPC network isolation, control-plane API authorization, TLS-based authentication, in-transit encryption and data-plane authorization.

High Availability

Amazon Managed Streaming for Kafka enables multi-AZ replication for Apache Kafka clusters on the AWS cloud. As already mentioned, Amazon MSK continuously monitors Kafka clusters and automatically replaces them in case of the component failure. 

You may also be interested in reading Using Kubernetes For Container Orchestration and Cloud Deployment

Closing Thoughts

Apache Kafka is an extremely useful software that possesses higher throughput and replication characteristics, making it ideal for tracking IoT sensors with high accuracy. Developers can also use it in combination with other tools like Flume, Spark, Flink, Storm, and HBase. However, using Amazon Managed Streaming for Kafka gives you better flexibility and elasticity to easily accomplish complex development and deployment tasks. 

Avail Our AWS Development Services To Streamline Your IT Operations

We are an experienced cloud app development company that specializes in building cloud-based live video streaming apps with custom features. Our development team is skilled at using Amazon MSK platform to build, deploy, and scale feature-rich cloud applications with Apache Kafka’s seamless real-time streaming capabilities. Our end-to-end AWS cloud services include design, development, deployment, scaling, and QA testing to ensure that your app performs smoothly across the supported devices.

Benefits of Automation Through Microsoft Azure IoT Suite

The internet of things has grown in popularity as the number of connected devices has increased considerably over the past few years. According to Gartner, the global IoT market is expected to grow to 5.8 billion endpoints by the end of 2020. Having said that, the compound annual growth rate will be 21% as compared to the previous year. The advent of smart home automation technologies has unlocked new business opportunities for IoT application development Services. 

When it comes to IoT app development, a majority of businesses prefer cloud computing services to develop a centrally-managed IoT application. To address the increasing requirements of IoT app development, cloud platforms like AWS, Microsoft Azure and Google Cloud (GCP) have come forth with their unique serverless offerings. That being said, Microsoft Azure is rightfully considered a leading service provider for cloud-based application development. The Azure IoT Suite enables developers to build, deploy, and launch scalable IoT solutions for varied business requirements.

At Oodles Technologies, we have gained vast experience in cloud-based IoT app development services. Our development team is skilled at using cloud platforms like AWS, Azure, and GCP to develop scalable IoT apps with custom features. In this blog post, we enumerate the main benefits of Azure IoT Suite for building enterprise-grade applications with central tracking and analytics capabilities. 

Also read How Startups Can Benefit From AWS IoT Core

An Introduction To Azure IoT Suite

Microsoft Azure is one of the fastest-growing cloud platforms for building IoT-based applications. According to Business Insider, it is the second largest cloud platform for IoT application development after AWS. Azure IoT Suite provides a comprehensive SaaS solution with a set of open-source SDKs to develop, scale, deploy, manage, and run user-centric IoT applications over a serverless cloud architecture.

Azure IoT Service At a Glance

Azure IoT Suite includes several independent cloud-based IoT services to address different types of project requirements. Let’s discuss these services and their significance in cloud-based IoT application development.

Azure IoT Central

Azure IoT Central is a cloud service that lets you connect the new and existing IoT devices to the Azure cloud. Furthermore, it enables developers to build a simple yet effective IoT app with real-time analytics capabilities. IoT central is extremely useful for decision makers who need a simple interface to track the connected devices and gain insights into data.

It provides several built-in templates based on the industry use cases to accelerate the development process and reduce time-to-market. Most importantly, it lets you integrate your IoT app seamlessly with the existing business infrastructure and third-party services. 

Azure IoT Hub

Azure IoT Hub lets you establish a reliable connection between Azure cloud and the IoT devices to facilitate a seamless communication. It is capable of handling billions of connected devices without affecting the cloud infrastructure. 

Developers can use Azure IoT Hub to securely channelize data between devices and establish a smooth two-way communication. It maintains a smooth flow of user commands from backend to the connected devices. At the same time, it ensures security and privacy of various communications through device registration, authentication, and message delivery authentication.

Azure IoT Edge

Azure IoT Edge enables enterprises to extend the capabilities of an IoT system with edge intelligence. The service lets you move some of your IoT data (including analytics and messages) to the edge computing devices. In this way, you can offload operations in the cloud, thereby reducing the bandwidth and overhead costs. It further accelerates the decision-making process and lets you operate offline as well. Above all, it facilitates provisioning and management of edge devices for better user convenience. 

You may also be interested in reading Building and Deploying ML Models On The Google Cloud

Benefits of Azure IoT Platform

Understandably, Azure IoT Suite offers some of the best services to develop, run, and manage IoT applications with better flexibility. Below are the main benefits of automation through Azure IoT Hub.

• Simplified coding interface
• Ready-to-use device templates
• Real-time data analysis and visualization
• Secure authorization and authentication
• Flexible pricing model
• Robust community support
• Easy integration with third-party services

Conclusion

The future of IoT and smart home automation looks bright and promising. With the increasing applications of connected devices and industry use cases, it seems evident that IoT could be a mainstream technology in the near future. At the same time, cloud platforms like AWS, Azure, and GCP continue to evolve, bolstering their support for the internet of things. 

Why Choose Oodles Technologies For Cloud-based IoT App Development?

We are a seasoned cloud app development company that specializes in building scalable IoT and smart home applications using the latest tools and technologies. Our development team holistically analyzes your project requirements and formulates effective strategies to build a performance-driven IoT app that streamlines business processes. We have successfully completed full-fledged IoT projects for our clients with a focus on cloud-based automation.