libLunchbox facilitates the development and deployment of multi-threaded applications. It provides OS Abstraction, using utility classes abstracting common operating system features (such as threads, locks, memory maps, shared library loading, and condition variables), high-performance primitives (including thread-safe utilities tuned for performance, such as atomic variables, spin locks, and lock-free containers), and utility classes (including helper primitives which are not in the standard library, such as logging, pools, and random number generation).
BlackRay is a relational database system designed to offer performance features commonly associated with search engines. It offers SQL support and sophisticated operational and management features. Load-balancing and operational stability by means of N+1 redundance are included. BlackRay is called a "Data Engine" since it combines traditional, relational database features and SQL with the power and flexibility of search engines. It is a true hybrid, offering transaction support, data-versioned snapshots, and sophisticated function-based indices. Wildcards, phonetic, and fuzzy logic searches are supported, as well. BlackRay supports a subset of the SQL92 standard and provides JDBC/ODBC/native driver options via the PostgreSQL protocol, in addition to an API based query option. The project is released under the GPLv2, with some drivers available under BSD-style licenses. Commercial support contracts are available as well.
Torrus is an alternative software platform to MRTG, Cricket, and Cacti. In most cases it brings more flexibility and performance. It is able to poll more than 50,000 SNMP OIDs every 5 minutes from a single moderately equipped server, with simultaneous threshold monitoring of half of them. Torrus is designed to be a universal data series processing framework. Its scalable hierarchical design, application-independent core, and highly customizable architecture make it an attractive choice both for small installations and for big enterprise or carrier networks. Although most users deploy Torrus for SNMP monitoring, it might be useful for data series of any nature. Tobi Oetiker's RRDtool is used for data storage.
gprog is a basic GUI pipe meter that shows the percentage complete as data moves through a Unix pipe. It is very fast because it uses a dual process design with a cache oblivious algorithm for self-tuning. Also, the presentation is largely decoupled from the transfer, so that the GUI won't slow down the transfer.
Pylot is a tool for testing the performance and scalability of Web services. It runs HTTP load tests, which are useful for capacity planning, benchmarking, analysis, and system tuning. It generates concurrent loads, verifies server responses, and produces reports with metrics. Tests suites are executed and monitored from a GUI or the shell.
RegressionSuite is a software test suite that incorporates measurements of startup lag and accurate execution times, generating execution statistics, customized input distributions, and processable regression specific details as part of the regular unit tests. It provides a framework around which the individual unit regressors are invoked (and details and statistics collected). Unit regressors are grouped into named regressor sets (or modules), and regressors are created by implementing specific regressor interfaces. These two features make regressors particularly amenable to testing analytics (and other similarly state-light) modules.
Metrix++ is a platform to collect and analyze code metrics. It has a plugin-based architecture, so it is easy to add support for new languages, define new metrics, and/or create new pre- and post-processing tools. Every metric has 'turn-on' and other configuration options. There are no predefined thresholds for metrics or rules; you can choose and configure any limit you want. It scales well to large codebases. For example, initial parsing of about 10000 files takes 2-3 minutes on an average PC, and only 10-20 seconds for iterative re-run. Reporting summary results and exceeded limits takes less than 1 - 10 seconds. It can compare results for 2 code snapshots (collections) and differentiate added regions (classes, functions, etc.), modified regions, and unchanged regions. As a result, easy deployment is guaranteed into legacy software, helping you to deal with legacy code efficiently, and either enforce the 'leave it not worse than it was before' rule or motivate re-factoring.
Django-live-profiler is a low-overhead data access and code profiler for Django-based applications. Profiling Web applications on a development environment often produces misleading results due to different patterns in the data, different patterns in user behavior, and differences in infrastructure. All existing DB access profiling solutions for Django seem to focus on a single request, but in the real world certain queries might be negligible in a single request while still putting a considerable strain the database across all requests. Django-live-profiler aims to solve these issues by collecting database usage data from a live application.