High availability hosting refers to hosting infrastructure and architectures designed to provide near 100% uptime and ensure continuous availability of applications and services. For many businesses today, especially those operating online or providing critical services, any amount of downtime can result in significant losses in revenue, productivity, and reputation. As such, designing and implementing highly available hosting architectures is a key priority.
Some key characteristics of high availability hosting include:
- Redundancy of critical components like servers, storage, and network connections to eliminate single points of failure.
- Automated failover between redundant components to keep services running in case of outages.
- Load balancing to distribute traffic across components for performance and failover.
- Rigorous monitoring and alerting to detect issues proactively before they cause downtime.
- Automated recovery procedures to rapidly restore services after failures or outages.
- Use of high quality hardware components to minimize failures.
- Geographic redundancy across multiple data centers to protect against localized outages.
Challenges of Ensuring High Availability
While the goals and key principles of highly available architectures may seem straightforward, designing and implementing them to work seamlessly and cost-effectively can be complex for several reasons:
- Eliminating single points of failure requires careful planning and redundant components which add costs. Striking the right balance can be difficult.
- Automating failover adds software and data synchronization complexities like managing synchronous vs asynchronous replication.
- Load balancing has to be adaptive and intelligent to distribute loads optimally across components.
- Rigorous monitoring and alerting infrastructure must be designed to proactively detect anomalies and trigger automated recovery workflows.
- Automated recovery procedures have to be crafted thoughtfully to bring systems to a properly synchronized state post-recovery.
- Software bugs, misconfigurations or compatibility issues can unexpectedly bring down systems and are hard to anticipate.
- Components from different vendors may not always interoperate seamlessly, complicating redundancy.
- Making redundant components work cohesively as a system requires thorough testing and tuning.
High Availability Hosting Architecture Patterns
Several common architecture patterns have emerged to help tackle the various complexities and challenges involved in designing highly available hosting infrastructures:
In an active-passive set up, the hosting architecture consists of two identical hardware components, with one being the primary active component handling all production traffic while the other remains on standby or passive. The passive component does not serve any traffic directly. In case the active component fails, the standby passive component automatically takes over serving traffic.
The active-passive model minimizes complexity as only one component is active at a time. However failover is not instantaneous and some requests may be dropped. Active-passive works well for read-heavy workloads which can tolerate some downtime.
In an active-active architecture, two or more identical hosting components simultaneously handle production traffic and user requests. A load balancer distributes requests across the active components. If one fails, traffic is simply routed to the remaining components.
Active-active setups provide faster failover as requests can be instantly redirected to surviving components. However, more complexity is involved in keeping components in sync and load balanced. Active-active suits read-write workloads requiring minimal downtime.
In N+1 clustering, a pool of N+1 identical hosting components work together to serve traffic. A load balancer distributes load across all N components. The +1 component remains on standby. If any of the active N components fail, the standby takes over immediately.
N+1 combines the redundancy of active-passive with the performance of active-active. It allows separating application processing from standby capacity. It can be costly to overprovision +1 standby capacity though.
Here, duplicate versions of hosting infrastructure are set up across two or more geographic regions or data centers. Traffic is actively handled by all regions simultaneously. If one region goes down, traffic is routed to the remaining region(s).
This protects against failures confined to one region like power outages or natural disasters. However, latency across regions can impact performance if not well managed.
High Availability Components
Some key components used in typical high availability architectures are:
Load balancers distribute incoming client traffic across multiple active hosting components and also perform periodic health checks. If any component becomes unavailable, the load balancer stops routing further requests to it. This provides redundancy and failover.
Organizations usually maintain redundant duplicate servers (physical or virtual machines) clustered together to eliminate single server dependencies. Automated failover moves operations to standby servers if any active server goes down.
Shared synchronized storage like SAN systems and virtualized cluster file systems is used to provide common data access across redundant servers. Synchronous replication ensures storage fails over rapidly.
Uninterrupted redundant power through battery backups and onsite generators maintains operations during power failures affecting primary grid power.
Redundant connections via multiple ISPs using different network paths ensures outbound connectivity remains available if one ISP experiences issues.
Authoritative DNS servers in diverse locations improves DNS resolution availability. DNS load balancing spreads requests across servers.
High Availability Service Architecture
For a complete highly available hosting service, high availability needs to be built into every layer of the service architecture:
Load Balanced Redundant Reverse Proxies
Incoming client traffic is distributed via load balancers across a pool of reverse proxies terminating TLS connections and handling L7 requests. Redundant proxies ensure no requests are disrupted.
Application Servers Under N+1 Clustering
Stateless horizontally scalable application servers like Nginx serve requests fanned out by the reverse proxies. A pool of N+1 application servers provides scalability and redundancy.
Databases like MySQL are clustered and replicated in active-passive or active-active mode to remove single database dependencies. Node failures trigger failover.
Shared Storage And SAN
Shared storage pools enable databases and applications to access common data consistently. SAN replication maintains storage availability.
Services are divided into isolated compartments ensuring failures are restricted from cascading across systems. Loose coupling minimizes dependencies.
By combining redundancy across layers of the architecture, overall system availability improves significantly.
High Availability on Public Clouds
Major public cloud platforms like AWS, Azure and Google Cloud make it easier to create highly available architectures by providing many managed services, abstraction and automation:
- Auto Scaling Groups automatically spawn additional instances as needed to maintain redundancy.
- Elastic Load Balancers seamlessly distribute inbound traffic across instances while handling failover.
- Managed database services like AWS RDS enable replication, clustering and redundancy more easily.
- Availability Zones provide geographic redundancy within regions protecting from localized outages.
- Templates and infrastructure-as-code tools automate deployment across regions and zones.
- Status dashboards provide visibility into operations and health of resources.
- Automatic recovery procedures restore configurations and restart failed instances.
While public clouds abstract much complexity, architects still have to make design choices keeping availability, performance and complexity trade-offs in mind depending on service needs.
High Availability Testing
Robust testing is crucial for ensuring highly available architectures maintain uptime as expected when failures occur:
Load Tests: Load tests validate performance remains unaffected when components failover and rebuild capacity under peak traffic volumes.
Failover Tests: Failover is triggered manually to test recovery procedures and confirm capacity balancing post-failover.
Fault Injection Tests: Faults are deliberately injected into components to validate redundancy and failover work end-to-end.
Disaster Recovery Tests: Entire services are failed over across geographic regions and restored to verify recovery procedures.
Monitoring and Alerting: Synthetic monitoring transactions validate uptime and performance from diverse locations. Alerting raises timely notifications when anomalies occur.
Continuous improvement of designs over multiple iterations under rigorous testing helps strengthen resilience and availability.
Delivering highly available hosting to support modern always-on applications can be challenging but crucial. Redundancy across infrastructure and service layers in conjunction with intelligent automation provides resiliency against inevitable failures. While cloud platforms simplify many aspects, architects still have to make practical trade-off decisions tailored to use cases. Comprehensive testing and monitoring completes the picture to ensure availability keeps pace with business demands.