The goal of Swagger is to define a standard interface for describing REST APIs. In an ideal world, a Swagger definition for your API will allow both humans and computers to discover and understand your API. At it’s core, Swagger is a formal specification of an API. Surrounding this specification are a wide swath of tools to support creating documentation, providing client libraries, and managing API deployments. One of Swagger’s original goal was to provide a way to document an API in both a human and machine readable way. Swagger provides such a documentation format for RESTful APIs. By augmenting this documentation format with tools for API clients and developers, Swagger grew into an ecosystem providing for API developers and consumers. ...

As someone who is being recently re-introduced to the Java platform, there are a lot of components and pieces to become familiar with. One of those pieces is OSGi, a service registry and deployment specification for Java apps. The OSGi specification describes a complete environment for running Java applications as components. Each component is a bundle that can be remotely installed, started, stopped, updated or uninstalled. In addition, OSGi provides a service registry that allows existing services to detect the addition or removal of other services and adapt accordingly. ...

Title and Author of Paper The Volcano Optimizer Generator: Extensibility and Efficient Search. Goetz Graefe and William J. McKenna. Summary The query optimizer’s job is to take user input in the form of SQL and generate a cost-efficient plan for satisfying that query using the underlying physical layout of the database. This paper describes Volcano, a system for taking a data model, logical algebra, physical algebra, and optimization rules and translating them into optimizer source code. ...

Title and Author of Paper Dynamo: Amazon’s Highly Available Key-value Store, DeCandia et al. Summary Dynamo, as the title of the paper suggests, is Amazon’s highly available key-value storage system. Dynamo only supports primary-key access to data, which is useful for services such as shopping carts and session management. Dynamo’s use case for these services is providing a highly-available system that always accepts writes. This requirement forces the complexity of conflict resolution to data readers. Writes are never rejected. ...

Amazon Simple Queue Service (SQS) is a message queue service that allows applications to reliably queue messages from one system component to be consumed by another component. Adding a queue between application components allows them to run independently, effectively decoupling applications by providing a buffer between producers of data and their consumers. Up and Running This section provides a guide to getting up and running with SQS using a fictional music store as an example. This music store has the ability to notify clients of any upcoming events via SQS. ...

Title and Author of Paper Cap Twelve Years Later: How the “Rules” Have Changed. Eric Brewer. Summary This article provides an exploration of the CAP Theorem and how it relates to database system design. The author argues that, since partitions are likely to happen, the system designer can introduce methods for safely recovering from partitions to compensate. This strategy allows the database to continue to provide availability during a partition, and enforce consistency once the partition is resolved. ...

When integrating two independent services you have two options: making a remote procedure call (RPC), or sending a message. Which should you choose? What is a Remote Procedure Call? An organization often needs to share data and processes between multiple independent processes in a responsive way. For example, updating a user’s name in a shipping system may trigger updates in a billing system. The shipping system could update the billing system’s data directly by modifying a shared database, but this approach requires the shipping system to know far too much about the internal processes of the billing system. Instead, the business system can encapsulate the update operation behind an interface in the form of a remote procedure call, or RPC. ...

A big portion of any software engineering revolves around integrating multiple, disparate applications into a cohesive and functional whole. These apps may be built in house or third-party, or they may run on your network or distributed geographically, or they may be microservices designed to integrate. In any of these cases, you have several different options for integration, each with pros and cons. The integration patterns listed here are ordered by least to most sophisticated, but also by least to most complex. ...

The request was fairly simple — iterate through some data and update some dates. Something as simple as this. for entry in db.query(): entry.date = entry.date + timedelta(days=10) entry.put() Unfortunately, the NoSQL database we were using did not support schemas and, unbeknownst to me, some data had been changed in unexpected ways on production. Something as simple as this. Notice the Outlier? My code seemed correct. Unit tests passed. Code review passed. It ran flawlessly on the test environment. QA signed off on the change. So we deployed it. And things broke. ...

Point-to-point communication between servers usually works just fine when one or two instances are communicating. One or two instances communicating However, if you increase the number of applications, the total number of connections increases. Three instances communicating In fact, the total number of connections increases as a square of the number of application instances. So, if you are running 100 instances, you will be maintaining O(100^2) connections. The scaling becomes quite painful. ...