Model serving architectures are systems designed to make machine learning models available for use after they have been trained. These architectures handle tasks such as receiving data, processing it through the model, and returning results to users or applications. They can range from simple setups on a single computer to complex distributed systems that support…
Category: AI Infrastructure
Model Versioning Systems
Model versioning systems are tools and methods used to keep track of different versions of machine learning models as they are developed and improved. They help teams manage changes, compare performance, and ensure that everyone is working with the correct model version. These systems store information about each model version, such as training data, code,…
Data Stream Processing
Data stream processing is a way of handling and analysing data as it arrives, rather than waiting for all the data to be collected before processing. This approach is useful for situations where information comes in continuously, such as from sensors, websites, or financial markets. It allows for instant reactions and decisions based on the…
ETL Pipeline Design
ETL pipeline design is the process of planning and building a system that moves data from various sources to a destination, such as a data warehouse. ETL stands for Extract, Transform, Load, which are the three main steps in the process. The design involves deciding how data will be collected, cleaned, changed into the right…
Multi-Cloud Load Balancing
Multi-cloud load balancing is a method of distributing network or application traffic across multiple cloud service providers. This approach helps to optimise performance, ensure higher availability, and reduce the risk of downtime by not relying on a single cloud platform. It can also help with cost management and compliance by leveraging the strengths of different…
Serverless Function Management
Serverless function management refers to the process of deploying, monitoring, scaling, and maintaining small pieces of code called functions on cloud platforms, without having to manage the underlying servers. This approach allows developers to focus on writing the code that handles specific tasks, while the cloud provider automatically handles the infrastructure, scaling, and availability. Serverless…
Cloud Resource Orchestration
Cloud resource orchestration is the automated coordination and management of different cloud computing resources, such as servers, storage, and networking. It involves using tools or software to organise how these resources are created, connected, and maintained, ensuring they work together efficiently. This process helps businesses deploy applications and services more quickly and reliably by reducing…
Log Analysis Pipelines
Log analysis pipelines are systems designed to collect, process and interpret log data from software, servers or devices. They help organisations understand what is happening within their systems by organising raw logs into meaningful information. These pipelines often automate the process of filtering, searching and analysing logs to quickly identify issues or trends.
Continuous Integration Automation
Continuous Integration Automation is a process in software development where code changes are automatically tested and merged into a shared codebase. This automation ensures that new code works well with existing code and helps catch errors early. It uses tools and scripts to automatically build, test, and sometimes deploy code whenever developers make changes.
Automated Workflow Orchestration
Automated workflow orchestration is the process of managing and coordinating tasks across different systems or software with minimal human intervention. It ensures that each step in a process happens in the correct order and at the right time. This approach helps organisations increase efficiency, reduce errors, and save time by automating repetitive or complex sequences…