Server deployment trends are constantly evolving as technology advances. Some of the major trends we are seeing right now include increased usage of cloud computing services, containerization, microservices architectures, and automation.
Cloud Computing
One of the biggest shifts in server deployment is the move to cloud computing services like AWS, Azure, and Google Cloud. The flexibility, scalability, and cost savings of public cloud services have led many organizations to migrate some or all of their workloads to the cloud.
According to RightScale’s 2019 State of the Cloud report, 94% of enterprises are now using public cloud services. The most commonly used services are infrastructure-as-a-service (IaaS) offerings like virtual machines and storage. Popular platforms include AWS EC2, Azure Virtual Machines, and Google Compute Engine.
In addition to public cloud services, many organizations are also utilizing private clouds and hybrid cloud architectures. Private clouds provide many of the benefits of public cloud computing behind a company’s firewall. Hybrid clouds allow businesses to run a mix of workloads across on-premises infrastructure and the public cloud.
Benefits of Cloud Computing
- Flexibility and scalability – Server capacity can be added or removed on demand to match workload requirements.
- Pay-as-you-go pricing – Organizations only pay for the infrastructure resources they consume.
- Faster time to deployment – New server resources can be spun up quickly without having to procure and configure hardware.
- Globally distributed – Applications can be deployed to cloud data centers around the world to be closer to users.
- Disaster recovery – Cloud services make it easier to deploy applications across multiple geographic regions for redundancy.
Containerization
Container platforms like Docker and Kubernetes are also gaining significant adoption for deploying server workloads. Containers allow applications to be packaged up with all their dependencies into standardized units that can be easily distributed and run on any infrastructure.
According to RightScale’s survey, 57% of enterprises are now using Docker containers, while adoption of orchestration tools like Kubernetes grew from 26% to 51% from 2018 to 2019.
Containers provide a number of advantages over traditional virtual machines:
- More efficient resource utilization – Containers share the host operating system instead of running their own complete OS image.
- Greater portability – Containerized applications can be deployed seamlessly across on-prem and cloud environments.
- Improved scalability and availability – Kubernetes provides easy scaling and load balancing of container workloads.
- Faster deployment cycles – Containers make CI/CD pipelines and DevOps workflows much easier to implement.
As a result of these benefits, many organizations are now turning to container platforms to deploy a wide variety of workloads, from web applications to big data analytics applications.
Microservices
The microservices architectural style is also gaining popularity for building and deploying cloud-native applications. With microservices, applications are broken down into independently deployable modular services that focus on specific business capabilities.
Microservices provide a number of advantages over traditional monolithic architectures:
- Better scalability – Individual services can be scaled up/down independently to meet demand.
- Faster deployment – Smaller codebases allow for more frequent updates and rapid innovation.
- Technology flexibility – Services can be implemented using different languages/technologies unlike monolithic apps.
- Resilience – If one service fails, the rest of the application continues to function.
- Organizational alignment – Teams can work independently on different services.
Major cloud providers like AWS and Azure now offer managed microservices platforms such as AWS Fargate and Azure Service Fabric. These make it easier to develop, deploy and manage containerized microservices in the cloud.
Infrastructure as Code
Infrastructure as code (IaC) is a practice that is enabling more consistent and automated server deployment. With IaC, infrastructure elements like networks, virtual machines, etc. are defined and provisioned through machine-readable definition files rather than manual processes.
This allows server environments to be quickly recreated in a predictable and repeatable way. IaC helps address many of the configuration drift and snowflake server challenges organizations face when managing infrastructure manually.
Popular IaC tools include:
- Ansible
- Chef
- Puppet
- Terraform
These tools allow ops teams to define infrastructure elements like networks, load balancers, VMs, etc. in simple declarative definition files. The IaC tools then automatically provision the infrastructure based on the definitions.
IaC enables DevOps practices like continuous delivery by standardizing and automating server provisioning. Infrastructure changes can easily be version controlled and deployed repeatedly across different environments like dev, test, staging, and production.
Automation
Increased automation is also a major trend across the server deployment lifecycle. Tasks that previously required extensive manual effort are now being automated to improve efficiency, reduce costs, and minimize configuration drift.
Some examples of increased automation include:
- Automated server patching and configuration management using tools like Ansible, Chef, and Puppet.
- Automated infrastructure provisioning and orchestration using Terraform, CloudFormation, etc.
- Automatic horizontal scaling of infrastructure resources based on monitored load metrics.
- Zero-touch server provisioning with tools like MAAS, Kickstart, etc.
- Automated CI/CD pipelines that build, test and deploy application updates.
These automation capabilities help streamline and simplify many complex operational processes involved in deploying and managing server infrastructure. The result is faster deployment times, reduced human errors, and improved efficiency for IT teams.
Security
With data breaches constantly in the news, security is top of mind for most IT organizations today. Some of the trends around enhanced infrastructure security include:
- Use of cloud provider security capabilities – Major cloud platforms offer a wide array of managed security services like encryption, role-based access, firewalls, malware detection, etc.
- Micro-segmentation and container isolation – Containers and microservices allow increased network segmentation to limit lateral movement in the event of a breach.
- Immutable infrastructure – Servers are treated as immutable objects that are routinely destroyed and recreated from a known good state.
- Automated security monitoring and remediation – Tools automatically monitor configurations and events for signs of compromise and take action.
Adopting modern deployment approaches like DevSecOps and security automation helps organizations address security throughout the IT lifecycle rather than just as an afterthought.
Increased Use of APIs
Another common trend is the increased use of APIs to enable automation and integrate infrastructure tools together into coordinated workflows. For example:
- Cloud provider APIs allow programmatic management of infrastructure resources like spinning up a VM instance.
- Container registries like Docker Hub have APIs for managing container images.
- Infrastructure definition tools utilize APIs to interface with various cloud platforms.
- Monitoring tools expose data collection APIs to gather metrics and events from infrastructure.
These APIs allow once manual processes to be integrated together into automated pipelines. They also enable infrastructure changes to be tracked and managed through centralized workflows rather than separate bespoke tools.
Monitoring and Observability
In today’s complex and dynamic environments, having good visibility into infrastructure and application state is critical. Some of the trends in monitoring and observability include:
- Granular metrics – The ability to collect fine-grained performance metrics on infrastructure components like servers, containers, etc.
- Log aggregation – Centralized aggregation of logs from across the infrastructure to enable analysis and auditing.
- Tracing and distributed request tracking – Following a request across microservices and infrastructure tiers.
- Visual dashboards – Intuitive graphical dashboards to monitor infrastructure health and performance.
- Alerting – Real-time alerts when specific events occur or thresholds are exceeded.
Advanced monitoring approaches help ops teams quickly identify issues, troubleshoot problems, and understand how changes impact the environment.
Edge Computing
Edge computing is a trend where processing and storage resources are located closer to the sources of data. This is important for use cases where latency needs to be minimized. Examples include:
- IoT devices that need to make real-time decisions based on data.
- Retail locations processing in-store data for personalized promotions.
- Smart city infrastructure like traffic lights adapting based on real-time car traffic.
- Autonomous vehicle data processing.
Public cloud providers are offering edge computing services like AWS Outposts and Azure Stack to support edge workloads. There is increased focus on simplifying deployment and management of infrastructure resources at edge locations outside of centralized data centers.
The Rise of Hybrid Multicloud
Many organizations are adopting a hybrid multicloud strategy that integrates both private cloud infrastructure in their own data centers along with public cloud platforms.
According to RightScale’s 2019 survey, around 82% of enterprises now have a hybrid cloud strategy. The average organization utilizes nearly five different cloud platforms. Microsoft Azure, Google Cloud Platform, and VMware vSphere are commonly used in addition to AWS.
A hybrid multicloud approach provides the most flexibility to deploy applications across the optimal platforms and migrate legacy resources. However, it also presents management challenges of monitoring and controlling infrastructure that is spread across many different providers.
Increased Use of AI and ML
Artificial intelligence and machine learning techniques are being increasingly embedded into infrastructure platforms and tools to add “self-driving” capabilities. For example:
- Cloud platforms use ML to automatically optimize resource utilization and placement.
- New servers can be automatically provisioned based on analyzed workload trends.
- ML models identify infrastructure issues and anomalies faster than manual techniques.
- Chatbots field common IT support queries without human agents.
Over time expect to see more AI/ML enhancements for things like predictive auto-scaling, intelligent workload placement, automated remediation, and personalized infrastructure recommendations tailored to each application.
Serverless Computing
Serverless computing platforms allow developers to deploy application code without having to manage the underlying infrastructure. The cloud provider automatically provisions, scales and manages the servers. Examples of serverless services include:
- AWS Lambda
- Azure Functions
- Google Cloud Functions
Serverless helps teams increase development velocity by removing infrastructure management overhead. It also allows services to scale to zero automatically to minimize resource costs when not in use. While still early, serverless adoption is growing quickly as organizations look to focus more on application code vs infrastructure management.
The Rise of DBaaS
Database-as-a-service (DBaaS) offerings that provide fully managed database services in the cloud are also gaining adoption. Top platforms include:
- Amazon RDS
- Azure SQL Database
- Google Cloud SQL
- MongoDB Atlas
DBaaS allows organizations to benefit from fully managed database servers without having to manually install, configure, and administer database software and infrastructure. DBaaS platforms make it easy to scale database capacity on demand while also handling tasks like backups, failovers, and security patching.
Increased Adoption of SaaS
In addition to infrastructure and database services, there is increased adoption of software-as-a-service (SaaS) alternatives to traditional on-premises applications. SaaS provides organizations the ability to utilize software that is hosted and managed centrally rather than installing and maintaining apps on site.
Common SaaS applications include:
- Office 365
- Salesforce
- Workday
- Box
- Zoom
- Slack
Benefits of SaaS include shifting the burden of hardware provisioning, software maintenance, security and uptime to the vendor. SaaS provides faster deployment times and lower upfront costs for gaining access to advanced software capabilities.
Everything as a Service
The combination of all these “as a service” models – IaaS, PaaS, DBaaS, SaaS, serverless, etc. – means organizations are increasingly becoming consumers rather than managers of technology infrastructure. The different components needed to power a modern application are being outsourced and integrated as services.
This allows technology teams to focus less on routine infrastructure management and more on developing applications aligned with business needs. It also allows organizations to leverage massive economies of scale by essentially “renting” infrastructure from large cloud providers rather than owning and operating data centers themselves.
The result is faster innovation speed for the business and ability to take advantage of new technologies much quicker than traditionally feasible.
Conclusion
In summary, some of the major trends influencing server deployment include:
- Adoption of public cloud and multicloud architectures
- Use of containers and container orchestration platforms
- Transition to microservices architectures
- Infrastructure as code and increased automation
- More advanced security capabilities
- APIs to integrate tools/platforms together
- Enhanced infrastructure monitoring and observability
- Edge computing for localized processing
- Incorporation of AI/ML enhancements
- Serverless computing
- DBaaS and SaaS alternatives to on-prem software
These trends reflect a broader shift towards more automated, programmable, and scalable infrastructure. There is less focus on physical hardware and more emphasis on software abstractions and application architectures aligned with business needs. Companies that embrace modern approaches are gaining significant agility advantages over organizations operating legacy infrastructure and processes.