When it comes to different concepts around data within software development, the concept of ephemeral data is gaining traction. But what exactly is ephemeral data, and why should you care?
Ephemeral data is temporary information that exists only for a short period or for a specific purpose. Think of it like a disappearing message or a fleeting snapshot of a moment in time. It offers numerous benefits, including increased privacy, improved security, and greater system efficiency.
In this blog post, we will explore ephemeral data, its characteristics, benefits, and practical applications. We’ll examine the differences between ephemeral and persistent storage and discuss how ephemeral data can help organizations balance data utility and data security. Let’s get started with a closer look at the core concept of ephemeral data.
What is Ephemeral Data?
Ephemeral data, by its nature, is temporary. This data typically has a pretty specific lifespan in terms of duration of time or purpose. In other words, ephemeral data typically exists only as long as it’s useful. After that, the data is processed through an automatic deletion mechanism that ensures the data is fully deleted. This data is typically not stored in a permanent location, but instead stored in ephemeral locations – this allows it to be highly efficient and much more private.
While the concept sounds complicated, it’s likely that you already have experience interacting with ephemeral data even if you’re not aware of it. Network buffers, for example, are ephemeral data that is used during data transmission to ensure that data is transferred in a retrievable and fault tolerant way. Session cookies are ephemeral data stored during a web session to allow sites to know who you are and provide persistent login.
In a more complex form, you might even have interacted with ephemeral data such as sensor data. Sensors in IoT devices, such as door locks, front doorbells, etc. may only provide ephemeral access to real-time data from IoT devices to interact with them in the immediate timeframe, erasing that data due to low storage provision.
Why is Ephemeral Data Important?
Ephemeral data is a critical piece of network infrastructure, especially in the modern connected device landscape where privacy, security, and high-efficiency are becoming more and more important by the day.
Let’s dig into some of the reasons ephemeral data is so important.
Ephemeral Data is (or Can Be) More Private
Ephemeral data is typically more private than long-term data storage. Because the data is not stored permanently, properly secured ephemeral systems minimize the risk of data exposure by reducing the total amount of access.
Bypassing the preservation stage of data generation means that a lot of the negatives of data collection are lost during deletion, preserving anonymity and reducing the likelihood of data being stolen. This all requires a proper security posture to be a true benefit, of course, but with proper tooling, ephemeral data is typically more private than non-ephemeral data.
While ephemeral data offers increased privacy by minimizing the time data is stored, it’s crucial to remember that ‘ephemeral’ doesn’t automatically equate to ‘secure’. If proper security measures aren’t in place, ephemeral data can still be vulnerable. For example, if data isn’t encrypted during transmission or while residing in memory, it could be intercepted by malicious actors. Similarly, if the deletion process is not secure, data remnants might be recoverable. Therefore, a holistic and comprehensive security strategy, including encryption, access controls, and secure deletion protocols, is essential to truly realize the privacy and security benefits of ephemeral data.
Benefits to Security
Since ephemeral data is by its nature short-lived, using it widely limits the attack surfaces exposed to potential threat actors and third parties. Reducing the number of records available on-hand can significantly reduce the potential damage due to breaches, and can mitigate long-term risks such as replay, impersonation, etc.
It’s important to remember that, to reap this benefit, the approach must be holistic – preservation of metadata while deleting the core data, for example, is only quasi ephemeral in nature, and could undermine gains to security overall. This means it is crucial to consider metadata when dealing with ephemeral data. Metadata, which describes the data, can inadvertently reveal sensitive information even if the actual data is deleted. For instance, metadata associated with a chat message might include timestamps, user IDs, and location information, which could be exploited. To mitigate this risk, organizations should implement techniques like data masking, anonymization, or pseudonymization to protect sensitive metadata.
Increased System Efficiency
Ephemeral data doesn’t occupy long-term storage stores, which ultimately saves resources. Companies utilizing ephemeral data typically find approaches such as serverless or cloud bursting to be preferable to on-premises data storage and processing, which can have significant impacts to overall operational costs.
Additionally, using ephemeral data can have huge benefits to the codebase, allowing for processes and capabilities that are focused on using relevant and live data rather than storing data long-term for reuse, remixing, and recontextualization. This can have huge benefits to the size, scope, and process cost of the internal codebase.
Adherence to Internal Policies, Legal Requirements, and Regulatory Compliance
Ephemeral data can have significant benefits in the realm of policy-driven compliance.
In the case of internal policies, ephemeral data can help ensure adequate protection for sensitive information by making sure data is not left exposed or vulnerable on the system.
For legal requirements, metadata can be preserved in an anonymous way while the core data is deleted, allowing for the protection of consumers while ensuring legal adherence.
For regulatory compliance, such as those required under the General Data Privacy Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA), ephemeral data can ensure compliance and reduce potential exposure of data at rest, sidestepping huge data security and privacy concerns.
Key Characteristics of Ephemeral Data
Ephemeral data has some key characteristics regardless of how it is functionally deployed.
Short Lifespan
Ephemeral data is, by its nature, something only exists temporarily. It is typically deleted or rendered inaccessible after a specific timeframe has elapsed or a specific use case is no longer applicable.
Non-Persistent
This data is non-persistent – in other words, the data is not stored permanently in databases or file systems. While this introduces more parts for a company to manage at scale, it does result in lower costs to businesses by limiting the scope and demand of storage technology on-site or in the cloud.
Context-Specific
Ephemeral data is often tied to a specific event, session, or process, with the data losing its purpose once that need is fulfilled. This data is often used to facilitate or establish connections between systems, stored the state of a given tool, provide statefulness to mobile devices, etc.
Lightweight
Ephemeral data is typically quite small, as it is designed for temporary use. This makes it a highly efficient method to send messages, secure sensitive communications, etc., as the data makes efficient use of encryption in transit and is not stored locally beyond its immediate use case.
Volatile and Secure by Design
Ephemeral data is meant to be volatile – is is extremely temporary, and as such, leaves little in the way of identifying information, sensitive data, or relevant documents on the system post-erasure. This transient nature, wherein the data only exists for a set period, ensures that private or high value information is protected through almost immediate erasure and the avoidance of long-term storage.
Non-Reliance on Storage
Because of this avoidance of long-term storage, ephemeral data does not have high storage needs and costs. Since this data largely resides in memory or other volatile storage media, this can drive down operational costs for organizations while ensuring that they are still able to collect data for functional purposes.
Limited Accessibility
Once the data is deleted, it typically cannot be retrieved. This limits access significantly, protecting the business value of the data while ensuring that users with high demands for securing electronically stored information – such as the federal government, health information technology providers, etc. – can secure their data from outside threats. While the limited accessibility of ephemeral data enhances security, it can present challenges for data recovery, auditing, and compliance requirements. Organizations need to carefully balance the need for security with the need for data retention and accessibility. This might involve implementing secure logging or backup mechanisms for critical ephemeral data while ensuring compliance with data retention policies and regulations.
Ephemeral Storage vs Persistent Storage
Because ephemeral data is so different from persistent data, their storage methods are often quite different and bear some consideration.
Ephemeral Storage
Ephemeral storage refers to temporary storage that exists only for the duration of a specific session, process, or instance. This storage typically utilizes memory or other volatile memory as opposed to hard drives and solid state disks, although those systems are sometimes used in conjunction with ephemeral container-based solutions as an alternative.
Characteristics
Ephemeral storage is:
- Temporary – data is only stored as long as it is needed, typically in a single session, process, or instance use case.
- Optimized for speed – ephemeral data is typically optimized for speed rather than durability, and as such, the storage for that data is likewise focused more on access and speed than longevity.
- Use specific – ephemeral data is often purposed for specific reasons – e.g., caching, temporary files, real-time processing, etc. – and as such, the storage that supports this data is likewise engineered for those specific use cases.
Examples of Ephemeral Storage
- Memory caching – tools like Regis or Memcached allow for data to eb stored and retrieved in volatile memory, allowing for rapid caching.
- Container storage – temporary storage pools for Docker or Kubernetes allow data that disappears once the container stops.
- Cloud-based storage – temporary storage in the cloud can be spun up or spun down as needs change.
Persistent Storage
Persistent storage refers to storage that retains data even after the associated session, process, or instance ends. This storage is non-ephemeral in nature.
Characteristics
- Long-term – this data is retained for multiple use cases, and is typically stored permanently or until deletion is specifically enacted.
- Optimized for reliability – data must be resilient to restarts, crashes, shutdowns, etc., and often have backups to ensure reusability.
- Focused on access – this data is often stored on-premises, or, at the very least, has local backups for ensuring access.
Examples of Persistent Storage
- Hard drive disks and solid state drives – traditional media storage is persistent in nature, surviving multiple use instances.
- Cloud storage – services like Amazon S3, Google Cloud, or Azure Blob Storage allow for cloud-based persistent storage.
- Databases – databases are largely a great example of persistent storage, as they are meant to be used over time repeatedly with the same data points and references.
Key Differences
| Feature | Ephemeral Storage | Persistent Storage |
| Lifespan | Temporary | Long-term or permanent |
| Retention | Data lost after process/session | Data retained after a session ends |
| Location | Often in-memory or local instance | Disk, cloud, or database systems |
| Performance | High speed | Moderate to high speed |
| Resilience | Not resilient | Resilient to failures and reboots |
| Use Cases | Caching, temporary files, session data | Databases, backups, logs |
Challenges of Ephemeral Data
The primary reason ephemeral data is not more widespread in staging and ephemeral environments alike is the generation or ‘copying-over’ of the data. This problem exists with persistent data systems as well. Typical methods of bringing over data are insufficient, as they contain expired security tokens, old timestamps, and don’t factor in idempotency or data persistence across multiple calls.
Collating data values across multiple services and understanding patterns without delving into the architectural structure of an application is extremely difficult. Beyond traditional batching and ETL processes, there are new emerging methods that allow ephemeral data:
Database virtualization
Database virtualization works by creating an abstraction layer between the physical database systems and the users or applications accessing them. This layer consolidates data from multiple sources, enabling seamless interaction as if all data were stored in a single, unified database.
The process begins with a virtualization engine that connects to multiple underlying databases, which could be hosted on-premises, in the cloud, or across hybrid environments. This engine retrieves data from these sources and presents it in a consistent format, often using metadata to manage how and where data is stored.
When a user or application queries the virtualized database, the virtualization engine translates the query into subqueries. These subqueries are executed on the relevant source systems, and the results are combined and delivered as a unified response. This ensures real-time access to distributed data without physically duplicating or moving it.
Database mocking
Database mocking works by creating “mock” databases or components that replicate the behavior of a real database without requiring access to the actual system. Developers use these mocks to simulate queries, transactions, and responses during testing. This approach eliminates the need for a live database, enabling faster and more isolated testing. Mocking is often implemented through libraries or frameworks that generate predictable, predefined responses to mimic specific database behaviors.
For example, a mocked database might simulate a query that returns customer information. Instead of connecting to a live production or test database, the mock simply provides the expected result. This reduces dependency on complex environments and ensures tests are consistent and repeatable.
In contrast, database virtualization works by connecting to real data sources and creating an abstraction layer to unify access. It doesn’t simulate data but provides real-time access to actual datasets.
Traffic-driven database mocks
An ideal balance between realism and agility is traffic-driven database mocks. This approach avoids the need to understand a physical database and and supporting an exhaustive matrix of database drivers and versions. It also avoids batch and ETL processes.
Traffic can be used to inform advanced data models using a set up machine learning rules or AI. Mocking them can allow fast tweaking and manipulation of data scenarios while providing a reliable substitute for the real systems.
Benefits of Ephemeral Data
Ephemeral data is a powerful way to ensure that you are using the relevant data for your ongoing processes without having collected data become a massive liability. Adopting effective ephemeral environments and ephemeral data-driven solutions requires some forethought, but when properly structured, these systems can provide timely and accurate data without the increased attack surface and threats that long-term data storage brings into the picture.
As an example of how this data can be extremely useful, we can look to Speedscale. Speedscale offers a great method for ingesting real data into ephemeral environments, allowing you to replicate real data in the development and testing pipeline. Ephemeral data in the form of traffic-driven database mocks can come into play as a secondary data source, allowing automated account actions or simulations to be compared in efficacy against actual traffic and identifying optimal flows versus the flows in the application.
This combined ephemeral and non-ephemeral data flow can also be put to good use with something like a bubble environment. These environments are essentially ephemeral, but have a slightly longer timespan and can be scaled to meet new needs. Combined with both ephemeral and static data storage, you can thus create environments that can rapidly scale and persist while using data that is non-persistent, giving you the best of both worlds!
Conclusion
Ephemeral data is incredibly powerful, offering everything from ephemeral messaging apps with disappearing messages protected by end to end encryption to Internet of Things signal driven solutions using temporary states. Ephemeral data gives you security and flexibility to meet changing demands on the network, and it does so using a solution that provides greater clarity, efficiency, and protection.
With an effective ephemeral plan and a solid analysis of your overall stack, any provider can get started with this approach in very little time – especially if you use a trusted partner like Speedscale that can provide ample support along the way.
If you are interested in trying out Speedscale in your ephemeral use case, you can get started with a free trial today! Users can sign up for a free 30-day trial of enterprise features – that’s everything you need to get started with ephemeral environments and data at scale!