Datamaker for Skytap. Provide full-sized environments filled with up-to-date test data in minutes

Transcription

1 Datamaker for Skytap Provide full-sized environments filled with up-to-date test data in minutes

2 Is your testing constrained by environments and data? As applications have become more complex, provisioning the right data to test and development environments has become a familiar pain point for many organizations. Environmental and data constraints quickly swallow time and resources, while defects go undetected, preventing the delivery of valuable software to market, on time and within budget. Environmental Constraints Many organizations rely on a limited number of shared environments, which take weeks to manually configure, and require much costly pre-production infrastructure. Often, development and QA teams settle for reproduced subsets of an overall system, but this leads to incomplete testing, and defects make it into production, causing time-consuming, late rework. Teams cannot work in parallel as they contend for the best environment and data, and bottlenecks quickly mount. On average: Medium-large organizations spends $12 million on pre-production infrastructure % of development and testing time is wasted due to a lack of environments 2 QA spend 30-50% of their time configuring environments 50% of IT capacity is spend on IT and development, which sits idle for 90% of the time Data Constraints Many organizations still provision production data to these environments, but this typically covers only 10-20% of tests that need to be run, and does not include future scenarios or unexpected results. It contains sensitive information, but manually copying and masking large sets of data is slow and errorprone, so that by the time data reaches teams, it is outdated. In fact, the average tester spends up to half their time wading through data for the specific combinations they need. The average tester spends 50% of their time wading through data for specific combinations 20% of the average SDLC is spent waiting for or manipulating data, or creating it by hand Defects found in production cost x more to fix than those found earlier The Solution: These environment and data constraints are why Grid-Tools and Skytap have teamed up, to combine powerful Environments-as-a-Service provisioning with end-to-end Test Data Management. Complete, production-like environments can be stored as templates and replicated in minutes, and are instantly populated with rich, up-to-date test data. Testing and development can begin instantly and in parallel, eliminating unnecessary delays and costs in the SDLC. 1 Virtual and Cloud-based Labs study, 2014, voke, inc. 2 Virtual and Cloud-based Labs study, 2014, voke, inc.

3 Instant full-sized Environments on demand With Skytap s EaaS you can: Reduce the time spent waiting for environments to minutes Store, copy or suspend complex systems anywhere, anytime, from a selfservice web portal Maintain full control over self-service provisioning using central dashboards, alerts, quotas and metrics. Repair defects up to 300% faster, by copying and sharing the exact environment they occurred in Shorten testing time, by providing teams distributed worldwide with complete environments in parallel Skytap s Environments-as-a-Service is the world s most advanced cloud-based solution for managing and delivering just-in-time software development and test environments. With Skytap, organizations can create representative development and QA systems, on demand. Complete, production-like systems can be stored as templates, cloned, and accessed in minutes using the Skytap web-portal. These are not just hardware images, but detailed configurations of multiple servers, appliances, network and domain settings, data, and virtual assets that can span multiple cloud instances. Teams can enjoy unconstrained, self-service access to isolated virtual machines anywhere, anytime, without requiring costly back-end systems or infrastructure. The issue of environment provisioning is therefore solved, and you deliver fully tested software to market earlier and at less cost.

4 Automatically generate the Right Data Automatically generate smaller, richer sets of test data with 100% coverage Eliminate bottlenecks caused when waiting for data to become available Reduce the time and resources required to provision data by up to 50% Detect defects earlier, and at less cost to fix, by covering all outlier data conditions and negative paths Test with smaller, richer sets of test data and reduce test environment infrastructure costs With Datamaker, these instant environments come filled with all the test data needed for complete testing. This eliminates the time spent waiting for, creating or searching for data, so that test cycles can begin instantly and in parallel. Using Datamaker, users can quickly model data stored across an entire enterprise, generating realistic synthetic data that provides 100% coverage. You can create smaller, rich sets of data for rigorous testing, reducing high environment infrastructure costs. Combinable data generation functions, bulking scripts and substitution variables will automatically create millions of rows of complex, up-to-date data, as fast as the database infrastructure can handle. This data includes future scenarios and unexpected results, allowing you to test boundary conditions and avoid the spiralling costs and delays caused when critical bugs are detected late.

5 Store data centrally in the Test Data Warehouse Store all your data pools centrally, and share it across teams in parallel Re-use data across versions and releases for efficient regression testing Eliminate delays and rework caused by data dependencies Assemble existing data objects into new or complex scenarios so that test teams have the data needed to fully test a system Extract subsets of production data, mask it and move it to test environments on demand The enhanced data is stored as re-usable assets in a central repository. Existing data and flat files stored across an organization can also be imported, before being stored and managed from a single location. Re-usable subsets of data can then be extracted, cloned, and delivered to environments on demand, eliminating data dependencies and maximizing the value of work done. Sophisticated version control means that relevant data sets automatically reflect and replicate changes made to system requirements, across projects and versions. Test and development teams can work with the most up-to-date data, developing multiple releases in parallel from stable, isolated environments. All the data needed to run efficient regression tests is preserved, while rare and interesting scenarios can be reserved, so that valuable data is not over-written by another team. This means that teams do not disrupt each other as they efficiently test and re-test an application.

6 The Right Data to the Right Place, at the Right Time Find and make the correct data automatically using the self-service Test Data on Demand web portal Automatically deliver data in minutes and avoid testing bottlenecks caused when searching for or manually creating data Drastically reduce the time and resources used to provision data Quickly mine fit for purpose data from multiple back-end databases, based on specific criteria Link data to specific test cases or directly into automated testing tools like HP ALM or IBM Rational Automated data discovery means that testers receive the data they need from multiple back-end systems in minutes, eliminating the 50% of time they otherwise spend looking for or preparing data, or creating it where none exists. They can request the exact data they need, having it automatically delivered from the central repository into their ideal state environments, in parallel and on demand. Dynamic form building enables testers to mine data using pre-defined criteria, rather than fixed values, using the Test Data on Demand web portal. This data is matched to the exact tests they need to run, so that testers can perform more stable tests, earlier, and with greater repeatability. Test teams can work in parallel and will defects, earlier, accelerating the delivery of fully tested software, at less cost to the business.

7 Copy and Extract coherent subsets of Test Data Avoid the prohibitively high costs of storing, copying and moving large copies of production data Test using small, rich subsets of test data and reduce infrastructure costs by up to $50k per database Maintain and re-use data after a refresh Run multiple test cycles in parallel to improve the agility of testing Clone and share bug scenarios, in the exact environment they occurred in to repair defects faster, and at less cost When a data set is provisioned, it is automatically cloned, so that the original data remains intact. This means that teams can work in parallel, while avoiding the slow and expensive process of manually copying and moving large copies of production data. Testing using intelligent subsets of data likewise reduces the infrastructure needed to store data, and can save as much as $50k per database. Delivering cloned data to isolated Skytap environments prevents bug scenarios being lost when one team makes a change. Instead, whole environments can be suspended, copied and shared worldwide, so that testers and developers can focus all their attention on improving an application, rather than reproducing the environment which a bug occurred in. Data is likewise preserved during a database refresh, so that you can run multiple test runs in parallel, delivering valuable software to market faster, and at less cost.

8 High Performance Data Masking Minimize the risk of costly data breaches by automatically finding and securing PII enterprise-wide Mask millions of rows of data in minute using native masking engines Eliminate reliance on inefficient ETL and in-house solutions Create masked services and messages in-flight for secure service visualization Provision compliant sets of test data to test teams and outsource providers in minutes Reduce bottlenecks caused by manual masking With Datamaker for Skytap, existing environments come filled with secure data, masked in flight, while existing data can be secured in minutes, mitigating risk while reducing the cost of compliance to the business. Datamaker provides powerful data profiling algorithms which will automatically discover potentially sensitive information stored enterprise-wide. 80+ combinable masking functions and four highperformance native masking engines will secure large, complex sets of data in minutes. Referential integrity and complex relationships will be maintained, producing data with all the characteristics of production, but none of the sensitive content. Data can also be masked in-flight for secure service and message virtualization, allowing teams to work in parallel, free from dependencies and constraints.

9 Realistic service and message virtualization Generate realistic virtual data for effective service virtualization and testing Mask data in-flight for secure service and message virtualization Create stable environments for SOA testing, free from cross-system dependencies and constraints Model existing services and map virtual traffic to new versions and releases Avoid project delays by simulating unavailable or incomplete components With Datamaker, teams can instantly access stable environments in which to rigorously test components of complex or unfinished applications using Skytap for API and REST calls. Testers can quickly generate realistic message and responses which cover the full range of scenarios, based on defined rules, recorded data models or templates. The virtual data includes structured and unstructured messages, as well as dummy service data for future scenarios and prototypes. This means that testing can begin immediately and in parallel, without having to wait for components to be completed or become available. A data model of existing services can further be frozen and stored in the Test Data Warehouse, so that virtual traffic can be mapped to separate versions. The data can be masked in-flight, so that outsourced teams and testers distributed worldwide can run efficient test cycles in parallel, without updating or exposing sensitive data.

10 F Contact us: Phone us: UK: +44 (0) USA: United Kingdom 11 Oasis Business Park, Stanton Harcourt Road, Eynsham, Oxfordshire, OX29 4TP USA Suite 320, 500 Mamaroneck Av., Harrison, New York Grid-Tool is headquartered in Oxford, UK, with offices in New York, USA, and an extensive network of global partners including Skytap, HP and CA Technologies. We are specialists in test data creation, data masking and test data management. Our experienced personnel have been writing and developing solutions for large companies in both the private and public sectors for over 30 years. Our personnel write and develop solutions for some of the largest corporations around the globe, from financial institutions to telecoms providers. Over the last decade, our innovative approach to test data management has helped radically improve how clients test and develop applications, delivering valuable software products on time and under budget. us: Phone us: USA: 1-(888) USA Suite 300, 719 2nd Av., Seattle, WA Skytap is headquartered in Seattle, Washington. Their clients include some of the world s biggest software organizations. They provides cloud-based software development and test environments for enterprises to deliver better software, faster. Today s enterprise is challenged to continuously deliver new customer-facing applications, while overcoming increasing change and complexity in their IT infrastructures. Our customers use Skytap to manage, import, deploy and decommission ondemand environments that contain everything needed to accelerate the software lifecycle, without unnecessary costs and project delays due to manual configuration and dependencies. Enterprise IT organizations maintain full visibility and cost control, while allowing dev and test teams to self-provision labs and share complex environments with ease for a lasting boost in agility.