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Observability - Wikipedia Observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. In control theory, the ... https://en.wikipedia.org/wiki/Observability

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What is Observability? | Splunk Observability is the ability to measure the internal states of a system by examining its outputs. A system is considered "observable” if the current state ... https://www.splunk.com/en_us/data-insider/what-is-observability.html

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What Full-Stack Observability Requires Today Observability is a lot more than a synonym for monitoring. Monitoring gives software teams instrumentation, collecting data about their systems and allowing ... https://newrelic.com/resources/ebooks/what-is-observability

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Observability: It's Not What You Think | Splunk May 4, 2021 ... What is Observability? ... Observability is a mindset that enables you to answer any question about your entire business through collection and ... https://www.splunk.com/en_us/blog/devops/observability-it-s-not-what-you-think.html

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Monitoring and Observability — What's the Difference and Why ... Apr 16, 2018 ... Basically, and as the definition states, it's a measure of how well internal states of a system can be inferred from knowledge of its external ... https://thenewstack.io/monitoring-and-observability-whats-the-difference-and-why-does-it-matter/

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Elastic Observability | Elastic Elastic Observability. Unified visibility across your entire ecosystem. Bring your logs, metrics, and APM traces together at scale in a single ... https://www.elastic.co/observability

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DevOps measurement: Monitoring and observability | Google Cloud Observability is tooling or a technical solution that allows teams to actively debug their system. Observability is based on exploring properties and patterns ... https://cloud.google.com/architecture/devops/devops-measurement-monitoring-and-observability

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Learn about observability | Honeycomb Observability is about being able to ask arbitrary questions about your environment without having to know ahead of time what you wanted to ask. Observability ... https://docs.honeycomb.io/getting-started/learning-about-observability/

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What is observability? | IBM Jan 12, 2021 ... In general, observability is the extent to which you can understand the internal state or condition of a complex system based only on knowledge ... https://www.ibm.com/cloud/learn/observability

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Intelligent observability | Dynatrace Turn data into answers, through intelligent observability. Remove blind spots, resolve problems rapidly and deliver superior customer experience. Start… https://www.dynatrace.com/platform/observability/

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Intelligent observability | Dynatrace Turn data into answers, through intelligent observability. Remove blind spots, resolve problems rapidly and deliver superior customer experience. Start… https://www.dynatrace.com/platform/observability/

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Istio / Observability Observability · Metrics. Istio generates a set of service metrics based on the four "golden signals” of monitoring (latency, traffic, errors, and saturation). https://istio.io/latest/docs/concepts/observability/

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Welcome! — Splunk Observability Cloud documentation Observability Cloud provides a unified experience for collecting and monitoring metrics, logs, and traces from common data sources. https://docs.splunk.com/Observability/

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Application Monitoring and Observability | Sumo Logic Reduce downtime and solve customer-impacting issues faster with an integrated observability platform for all of your application data including logs, ... https://www.sumologic.com/solutions/application-monitoring/

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Monitoring and Observability. During lunch with a few friends in late ... Sep 4, 2017 ... That's not sexy enough anymore. — Observability, because rebranding Ops as DevOps wasn't bad enough, now they're devopsifying monitoring too. — ... https://copyconstruct.medium.com/monitoring-and-observability-8417d1952e1c

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Data Observability: The Next Frontier Of Data Engineering - Monte ... Aug 31, 2021 ... To keep pace with data's clock speed of innovation, data engineers need to invest in data observability, the next frontier of data ... https://www.montecarlodata.com/data-observability-the-next-frontier-of-data-engineering/

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Observability: A Complete Overview for 2021 - Lightstep There are three primary types of telemetry data through which systems are made observable. Logs – Structured or unstructured lines of text that are emitted by ... https://lightstep.com/observability/

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What is Enterprise Observability? - Instana May 17, 2021 ... The Muddy Messaging of Observability and Application Performance Management. Here's a question I get asked quite a bit: "How is Enterprise ... https://www.instana.com/blog/what-is-enterprise-observability/

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Observability is key to the future of software (and your DevOps ... Sep 8, 2021 ... Observability platforms enable you to easily figure out what's happening with every request and to identify the cause of issues fast. https://stackoverflow.blog/2021/09/08/observability-is-key-to-the-future-of-software-and-your-devops-career/

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What Is Observability in Software? Learn More From Honeycomb Observability in software is the ability to understand and explain any state a system can get into without deploying new code. https://www.honeycomb.io/what-is-observability/

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Observability: What IT should know as the technology heats up ... Feb 18, 2021 ... As modern software systems become more and more complex, gaining observability into how applications perform and what makes them fail is ... https://www.infoworld.com/article/3608249/observability-what-it-should-know-as-the-technology-heats-up.html

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Observability | Dapr Docs Observability. Monitor applications through tracing, metrics, logs and health. When building an application, understanding how the system is behaving is an ... https://docs.dapr.io/concepts/observability-concept/

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Towards platform observability | Internet Policy Review Dec 18, 2020 ... This article proposes the concept of platform observability to help systematically study complex algorithmic systems. https://policyreview.info/articles/analysis/towards-platform-observability

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Rise of Full-Stack Observability | AppDynamics Read our Agents of Transformation 2021 report on the rise of full-stack observability and learn how technologists can manage soaring IT complexity by ... https://www.appdynamics.com/resources/reports/rise-of-full-stack-observability

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What is Observability? - Cribl How do you determine your needs with Observability? Understanding the Environment You're In; Asking Questions About Your Data; Structuring Your Data; Finding ... https://cribl.io/observability/

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Observability of complex systems | PNAS Feb 12, 2013 ... The observability criteria can be formulated algebraically for dynamical systems consisting of polynomial or rational expressions (1, ... https://www.pnas.org/content/110/7/2460

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VMware Tanzu Observability by Wavefront | VMware Tanzu From smarter, proactive alerting to instant custom metrics, VMware Tanzu Observability by Wavefront delivers enterprise-grade cloud monitoring & analytics. https://tanzu.vmware.com/observability

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Free eBook: Observability with AIOps For Dummies | Download Now Combine AIOps algorithmic analysis and automation with observability's detailed operational data. Written clearly and with a sense of humor by AIOps aficionado ... https://info.moogsoft.com/ebook-observability-aiops-for-dummies.html

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Observability Synonyms, Observability Antonyms | Merriam-Webster ... 18 synonyms and near synonyms of observability from the Merriam-Webster Thesaurus, plus 10 antonyms and near antonyms. Find another word for observability. https://www.merriam-webster.com/thesaurus/observability

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Domain-Oriented Observability Apr 9, 2019 ... Observability in our software systems has always been valuable and has become even more so in this era of cloud and microservices. https://martinfowler.com/articles/domain-oriented-observability.html

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Full Stack Observability Exam Do you know Observability on the New Relic platform? Put your knowledge to the test with our Full-Stack Observability Exam. https://learn.newrelic.com/full-stack-observability-exam

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Observability at Twitter Sep 9, 2013 ... Twitter's Observability stack is a distributed system just like the systems it provides visibility into. About 1.5% of the machines in a data ... https://blog.twitter.com/engineering/en_us/a/2013/observability-at-twitter

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Nonlinear controllability and observability | IEEE Journals & Magazine The properties of controllability, observability, and the theory of minimal realization for linear systems are well-understood and have been very useful in ... https://ieeexplore.ieee.org/document/1101601

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cncf/tag-observability: Technical Advisory Group for ... - GitHub Mission statement. The TAG Observability focuses on topics pertaining to the observation of cloud native workloads. Additionally, it produces supporting ... https://github.com/cncf/tag-observability

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Moral Hazard and Observability Moral hazard and observability. Bengt Holmstrom. Swedish School of Economics and Business Administration. The role of imperfect information in a ... https://www.jstor.org/stable/3003320

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Observability vs. Monitoring - A Guide for IT Operations | Devo.com Observability is the practice of achieving actionable insights from data that is generated by instrumented IT and software systems. https://www.devo.com/observability-vs-monitoring-guide/

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IT Observability Research Report | LogicMonitor Achieving unified observability in the age of digital transformation and technological convergence. https://www.logicmonitor.com/resource/it-observability-research-report

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Observability and Management for Cloud and IT environments | Oracle Oracle Cloud Observability and Management Platform. Oracle provides visibility and machine learning-driven actionable insights to ease management across all ... https://www.oracle.com/manageability/

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Observability | Grafana Labs Observing Loki Both Loki and Promtail expose a /metrics endpoint that expose Prometheus metrics. You will need a local Prometheus and add Loki and Promtail ... https://grafana.com/docs/loki/latest/operations/observability/

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Observability Report Page Jun 17, 2020 ... Contrast's 2020 Application Security Observability Report. Discover what are the top vulnerabilities and attacks over the past 12 months. https://www.contrastsecurity.com/appsec-observability-report-promo

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current editor: ?
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      network structure:
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      Network Structure Insights
       
      mind-viral immunity:
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      The higher is the network's structure diversity and the higher is the alpha in the influence propagation score, the higher is its mind-viral immunity — that is, such network will be more resilient and adaptive than a less diverse one.

      In case of a discourse network, high mind-viral immunity means that the text proposes multiple points of view and propagates its influence using both highly influential concepts and smaller, secondary topics.
      The higher is the diversity, the more distinct communities (topics) there are in this network, the more likely it will be pluralist.
      The network structure indicates the level of its diversity. It is based on the modularity measure (>0.4 for medium, >0.65 for high modularity, measured with Louvain (Blondel et al 2008) community detection algorithm) in combination with the measure of influence distribution (the entropy of the top nodes' distribution among the top clusters), as well as the the percentage of nodes in the top community.

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      Narrative Influence Propagation:
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      The chart above shows how influence propagates through the network. X-axis: lemma to lemma step (narrative chronology). Y-axis: change of influence.

      The more even and rhythmical this propagation is, the stronger is the central idea or agenda (see alpha exponent below ~ 0.5 or less).

      The more variability can be seen in the propagation profile, the less is the reliance on the main concepts (agenda), the stronger is the role of secondary topical clusters in the narrative.
      propagation dynamics: | alpha exponent: (based on Detrended Fluctuation Analysis of influence) ?   show the chart
      We plot the narrative as a time series of influence (using the words' betweenness score). We then apply detrended fluctuation analysis to identify fractality of this time series, plotting the log2 scales (x) to the log2 of accumulated fluctuations (y). If the resulting loglog relation can be approximated on a linear polyfit, there may be a power-law relation in how the influence propagates in this narrative over time (e.g. most of the time non-influential words, occasionally words with a high influence).

      Using the alpha exponent of the fit (which is closely related to Hurst exponent)), we can better understand the nature of this relation: uniform (pulsating | alpha <= 0.65), variable (stationary, has long-term correlations | 0.65 < alpha <= 0.85), fractal (adaptive | 0.85 < alpha < 1.15), and complex (non-stationary | alpha >= 1.15).

      For maximal diversity, adaptivity, and plurality, the narrative should be close to "fractal" (near-critical state). For fiction, essays, and some forms of poetry — "uniform". Informative texts will often have "variable + stationary" score. The "complex" state is an indicator that the text is always shifting its state.

      Degree Distribution:
        calculate & show   ?
      (based on kolmogorov-smirnov test) ?   switch to linear
      Using this information, you can identify whether the network has scale-free / small-world (long-tail power law distribution) or random (normal, bell-shaped distribution) network properties.

      This may be important for understanding the level of resilience and the dynamics of propagation in this network. E.g. scale-free networks with long degree tails are more resilient against random attacks and will propagate information across the whole structure better.
      If a power-law is identified, the nodes have preferential attachment (e.g. 20% of nodes tend to get 80% of connections), and the network may be scale-free, which may indicate that it's more resilient and adaptive. Absence of power law may indicate a more equalized distribution of influence.

      Kolmogorov-Smirnov test compares the distribution above to the "ideal" power-law ones (^1, ^1.5, ^2) and looks for the best fit. If the value d is below the critical value cr it is a sign that the both distributions are similar.
      ×  ⁝⁝ 
                 
      Main Topical Groups:

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      +     full stats   ?  

      The topics are the nodes (words) that tend to co-occur together in the same context (next to each other).

      We use a combination of clustering and graph community detection algorithm (Blondel et al based on Louvain) to identify the groups of nodes are more densely connected together than with the rest of the network. They are aligned closer to each other on the graph and are given a distinct color.
      Most Influential Elements:
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      +     Reveal Non-obvious   ?

      We use the Jenks elbow cutoff algorithm to select the top prominent nodes that have significantly higher influence than the rest.

      Click the Reveal Non-obvious button to remove the most influential words (or the ones you select) from the graph, to see what terms are hiding behind them.

      The most influential nodes are either the ones with the highest betweenness centrality — appearing most often on the shortest path between any two randomly chosen nodes (i.e. linking the different distinct communities) — or the ones with the highest degree.
      Network Structure:
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      Reset Graph   Export: Show Options
      Action Advice:
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      Structural Gap
      (ask a research question that would link these two topics):
      N/A
      Reveal the Gap   Generate a Question   ?
       
      A structural gap shows the two distinct communities (clusters of words) in this graph that are important, but not yet connected. That's where the new potential and innovative ideas may reside.

      This measure is based on a combination of the graph's connectivity and community structure, selecting the groups of nodes that would either make the graph more connected if it's too dispersed or that would help maintain diversity if it's too connected.

      Latent Topical Brokers
      :
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      These are the latent brokers between the topics: the nodes that have an unusually high rate of influence (betweenness centrality) to their freqency — meaning they may appear not as often as the most influential nodes but they are important narrative shifting points.

      These are usually brokers between different clusters / communities of nodes, playing not easily noticed and yet important role in this network, like the "grey cardinals" of sorts.

      Emerging Keywords
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      Evolution of Topics
      (frequency / time) ?
      The chart shows how the main topics and the most influential keywords evolved over time. X-axis: time period (split into 10% blocks). Y-axis: cumulative frequency of occurrence.

      Drag the slider to see how the narrative evolved over time. Select the checkbox to recalculate the metrics at every step (slower, but more precise).

       
      Main Topics
      (according to Latent Dirichlet Allocation):
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       ?  

      LDA stands for Latent Dirichlet Allocation — it is a topic modelling algorithm based on calculating the maximum probability of the terms' co-occurrence in a particular text or a corpus.

      We provide this data for you to be able to estimate the precision of the default InfraNodus topic modeling method based on text network analysis.
      Most Influential Words
      (main topics and words according to LDA):
      loading...

      We provide LDA stats for comparison purposes only. It works with English-language texts at the moment. More languages are coming soon, subscribe @noduslabs to be informed.

      Sentiment Analysis

      positive: | negative: | neutral:
      reset filter    ?  

      We analyze the sentiment of each statement to see whether it's positive, negative, or neutral. You can filter the statements by sentiment (clicking above) and see what kind of topics correlate with every mood.

      The approach is based on AFINN and Emoji Sentiment Ranking

      Sentiment analysis works for English language only. Contact us @noduslabs to propose a language and to get updated about the new features.

      Network Statistics:
      Show Overlapping Nodes Only

      ⤓ Download as CSV  ⤓ Download an Excel File

      Top Relations / Bigrams
      (both directions):

      ⤓ Download   ⤓ Directed Bigrams CSV   ?

      The most prominent relations between the nodes that exist in this graph are shown above. We treat the graph as undirected by default as it allows us to better detect general patterns.

      As an option, you can also downloaded directed bigrams above, in case the direction of the relations is important (for any application other than language).
      Please, enter a search query to visualize the difference between what people search for (related queries) and what they actually find (search results):

       
      We will build two graphs:
      1) Google search results for your query;
      2) Related searches for your query (Google's SERP);
      Click the Missing Content tab to see the graph that shows the difference between what people search for and what they actually find, indicating the content you could create to fulfil this gap.
      Find a market niche for a certain product, category, idea or service: what people are looking for but cannot yet find*

       
      We will build two graphs:
      1) the content that already exists when you make this search query (informational supply);
      2) what else people are searching for when they make this query (informational demand);
      You can then click the Niche tab to see the difference between the supply and the demand — what people need but do not yet find — the opportunity gap to fulfil.
      Please, enter your query to visualize the search results as a graph, so you can learn more about this topic:

       
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      Enter a search query to analyze the Twitter discourse around this topic (last 7 days):

           advanced settings    add data manually

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